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Study Find a course Analytics and Data Science Business Communication Design, Architecture and Building Education Engineering Health Health (GEM) Information Technology International Studies and Social Sciences Law Science and Mathematics Transdisciplinary Innovation Information for Undergraduate students Postgraduate students Graduate research students Studying online Short course and microcredential participants Indigenous Australians Students with accessibility requirements International students Current students Managing your course Your enrolment Fees and payment Your student info Classes and assessment Graduation Graduate research students Opportunities Scholarships, prizes and awards Global opportunities Community and leadership programs Career development Work opportunities Support Accessibility service Academic support Accommodation Health and wellbeing Financial help When things go wrong Studying from home Supporting online study portal Activities and social events Clubs and societies UTS Library Research and teaching Our research Explore our research Our approach Research centres Research excellence and support Find a UTS expert Graduate research Future research students New research students Current research students Supervisors and faculty Industry engagement programs Learning and teaching learning.futures UTS model of learning Learning and Teaching Grants Awards and citations Partner with us Our capabilities How to partner with us Commercialisation and IP Research careers Partners and community Working with UTS Partner with us Recruit our Talent Develop your staff Community Alumni and supporters Art gallery IELTS Centre Impact Studios Venues and facilities Signature events Initiatives Innovation and entrepreneurship Indigenous education and employment Internationalisation Social justice Sustainability Respect.Now.Always. Quick links Current students Staff International Alumni News Library Contact us Home About UTS Faculty of Engineering and Information Technology Research at the Faculty of Engineering and IT Research degrees and scholarships Research scholarships Research degrees and scholarships Research degrees Research scholarships Submitting an application Research degrees and scholarships Research degrees Research scholarships Submitting an application Research scholarships Find out more about the different scholarships and opportunities available for prospective Higher Degree Research candidates. Apply now READ THE how to apply guide Opportunities advertised below are specific to particular projects or research groups within the Faculty of Engineering and IT. To make an enquiry or to apply for an advertised project, please contact the person indicated. COVID-19 frequently asked questions Application deadlines Domestic candidates 2023 application deadlines to be advertised at a later date. SESSION APPLICATION DUE DATE COMMENCEMENT DATE Session 1 – 2022 30 September 2021 January 2022 Session 2 – 2022 30 April 2022 July 2022 International candidates 2023 application deadlines to be advertised at a later date. SESSION APPLICATION DUE DATE COMMENCEMENT DATE Session 1 - 2022 31 August 2021 January 2022 Session 2 - 2022 15 January 2022 July 2022 * The UTS competitive scholarship scheme will not be available for International Candidates in Research Session 1 2022. Sydney Quantum Academy Want a career in quantum technology? Applications are now open for Sydney Quantum Academy PhD Scholarships. Work alongside world-leading quantum experts, supported by a generous stipend of up to AU$35k pa. Scholarships offer access to the SQA PhD Experience Program which hosts a growing community of quantum PhD students from across Sydney. Students have the unique opportunity to undertake coursework across SQA’s four partner universities, including: the University of Technology Sydney, UNSW Sydney, Macquarie University, and the University of Sydney. SQA’s program provides specialised training, seminars, workshops and networking opportunities to gain a competitive edge in quantum’s future workforce. Apply by Sunday 26 September 2021. Visit Sydney Quantum Academy Biomedical Engineering Development of an In Vivo Model to Determine Neural Cell Responses to Silicon Nitride Wear Debris from Spinal Devices Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor Joanne Tipper Duration: 3 years (possible 6-month extension) School: School of Biomedical Engineering Centre: Centre for Health Technologies Closing date: when filled Domestic and International applications accepted. The incidence of spinal surgery, including the implantation of devices and/or instrumentation, continues to rise. Despite the perceived successes of spinal surgery, a number of significant challenges remain for the use of Motion Preservation Devices (MPD) and Spinal Instrumentation (SI) that include: (1) A younger patient profile (2) Significant issues with revision surgery, implying that devices need to last for the lifetime of patients (3) The proximity of neural tissues (& major vessels), which may be damaged if devices no longer perform as intended. These challenges are particularly important if one considers that implants comprise structures that have a large number of interfaces, e.g. screw-rod interfaces. Each of these interfaces can release debris and ions within a tribo-corrosive environment. Recent evidence arising from metal-on-metal (MOM) hip devices has shown that the discharge of ions is equally as important in driving detrimental implant performance as the release of debris arising from the wear process. Psuedotumour-like masses have been reported in the literature associated with MOM spinal devices, which have led to neurological impairment. Driven by these key issues, and coupled with the observation that current pre-clinical testing methodologies and standards are not sensitive enough to predict biological failure mechanisms, the proposed programme of research aims to develop a deeper understanding of the biological responses that may occur to wear particles and ions, in order to produce more realistic preclinical testing tools. In particular, there are no standardized animal models to understand the whole system in vivo responses to wear particles over the longer term. The aim of this project is to develop a clinically relevant animal model of neurotoxicity caused by exposure to biomaterials from spinal devices and instrumentation. Graphene oxide-based antimicrobial hydrogel for antibiotic-free tissue regeneration Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Jiao Jiao Li Duration: 3 years (possible 6-month extension) School: School of Biomedical Engineering Closing date: when filled Domestic and International applications accepted. Bacterial infections and the development of resistance against antimicrobial agents pose substantial health risks in recent times. Excessive and improper administration of antibiotics in past decades played a major role in this crisis. In 2019 WHO declared that antimicrobial resistance (AMR) will cause the death of 10 million people every year by 2050, with two-thirds of these deaths due to Gram-negative pathogens. Notably, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Proteus mirabilis, Serratia marcescens and Staphylococcus aureus species are responsible for most of the clinical infections and thus form a major threat to human healthcare due to their multidrug resistance. To solve this public health crisis, novel antibacterial agents should be added to the arsenal to fight MDR pathogens, especially before they develop new resistance mechanisms against current sensitive antibiotics. Infection in both acute and chronic wounds may cause considerable morbidity, mortality, and increased costs. A tissue bacterial bioburden of greater than 1x105 (or at least 1x106 bacteria per gram of tissue) can be present without clinical signs of infection, and can deleteriously affect wound healing. Attempts at controlling the tissue bacterial bioburden have faced challenges. The most common approach to defend wounds from bacterial colonization is the application of a topical bacterial barrier dressing, which can be a physical barrier, such as films or surgical gauze that are gas permeable but capable of hindering liquids. Oral antibiotics and use of topical microbicidal ointment are also common for preventing bacterial colonization and subsequent biofilm formation, or for treating established infections. However, the main limitations of these typical strategies are delayed re-epithelialization or regeneration, and potentially development of drug-resistance. Hence, there is an urgent need for antibacterial dressings that are effective, non-toxic, low cost, and do not induce resistance. This study will directly address this medical need and have broad applications in society, industry and hospitals. Full multidisciplinary supervision team: Dr Jiao Jiao Li (main supervisor), Professor Joanne Tipper and Dr Javad Tavakoli. Identifying therapeutic oncogene in breast cancer by using CRISPR-liposome gene editing tool Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Wei Deng Duration: 3 years (possible 6-month extension) School: School of Biomedical Engineering Closing date: when filled Domestic and International applications accepted. An emerging technique of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) has revolutionised gene editing field by introducing an efficient platform for precise editing of genes. Viral vector is the current leading approach for CRISPR delivery in clinical trials. However, it offers a limited level of spatial and temporal control over the gene editing process, which caused undesired off-target effect of CRISPR reagents. Our multidisciplinary team has made significant advances in the development of liposomes for in vivo CRISPR delivery. In this project we will develop liposome-formulated CRISPR with cancer targeting function. We will also explore in vitro and in vivo anti-tumour function and underlying mechanism induced by gene loss. This PhD project is expected to add knowledge on how to overcome this major challenge (off-target effect) by engineering the liposome formulations and add new insights to CRISPR-based therapeutic approach for metastatic triple-negative breast cancer. The PhD student involved in this project will develop expertise which is central to the field of CRISPR-based gene editing and nanotechnology. He/she will be fully supported and trained by senior academics with various expertise in gene engineering, nanocarrier engineering and tumour biology. The student will also be exposed to components of IP generation and medical translation. The ideal candidate should have lab training experience in areas such as chemistry, biotechnology, or materials science. Machine Learning for Medical Imaging Diagnosis and Treatment Planning Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Adrian N. Bishop Duration: 3 years (possible 6-month extension) School: School of Biomedical Engineering Closing date: when filled Domestic and International applications accepted. This project will consider recurrent neural networks and deep learning for medical imaging-based diagnosis AND subsequent (on-going) treatment planning and outcome prediction. Both human-machine cooperative planning and purely machine-only autonomous treatment planning from machine learning-based image diagnosis will be considered. A strong background in mathematical modelling, statistics and machine learning is essential. Modelling and simulation of cellular ion channel dynamics Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Adrian N. Bishop Duration: 3 years (possible 6-month extension) School: School of Biomedical Engineering Closing date: when filled Domestic and International applications accepted. This project will focus on the development of cellular ion channel models both from a deterministic and stochastic perspective. This is a mathematical sciences project with a focus on artificial intelligence and data driven methods for modelling and simulation. Many ion channel models are complex with a large number of states, and they need to be calibrated in terms of transition rates. The student will investigate such as issues as model identifiability to determine, based on realistic data sets, whether such models need this level of complexity or whether simplified data driven models can be constructed that can still predict important features. The main application focus will be on cardiac myocytes as ionic models are well developed and in many cases complex in nature. The student should have good skills in mathematical modelling, statistics, machine learning and/or related fields. Neural Cell Responses to Silicon Nitride Wear Debris from Spinal Devices Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor Joanne Tipper Duration: 3 years (possible 6-month extension) School: School of Biomedical Engineering Centre: Centre for Health Technologies Closing date: when filled Domestic and International applications accepted. The incidence of spinal surgery, including the implantation of devices and/or instrumentation, continues to rise. Despite the perceived successes of spinal surgery, a number of significant, synergistic challenges remain for the use of Motion Preservation Devices (MPD) and Spinal Instrumentation (SI) that include: (1) A high demand environment – largely due to the younger patient profile (2) Significant issues with revision surgery, implying that devices need to last for the patient’s remaining lifetime (3) The proximity of neural tissues (& major vessels), which may be damaged if devices no longer perform as intended. These challenges are particularly important if one considers that most implants comprise of structures that have a large number of interfaces, e.g. screw-rod interfaces. Each of these interfaces can release debris and ions within a tribo-corrosive environment. Recent evidence arising from metal-on-metal (MOM) hip devices have shown that the discharge of ions is equally as important in driving poor implant performance as the release of debris arising from the wear process. Psuedotumour-like masses have been reported in the literature associated with MOM spinal devices, which have led to neurological impairment. Ceramics are known to be well tolerated in vivo with ceramic wear particles from hip replacements having favourable biocompatibility profiles. Coatings have also been shown to reduce ion release from metal surfaces in devices, reducing adverse cellular responses to wearing products. Building on the work of a large EU FP7 project LifeLongJoints (www.lifelongjoints.eu) which investigated the use of SiN coatings in the bearing surface and taper junction of hip joint replacements, this project aims to investigate silicon nitride (SiN) containing coatings and bulk SiN ceramic materials for use in spinal devices in order to improve patient safety and enhance in vivo survivorship times of devices. Novel engineering solutions to cure back pain Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Javad Tavakoli Duration: 3 years (possible 6-month extension) School: School of Biomedical Engineering Closing date: when filled Domestic and International applications accepted. Low back pain is a leading cause of disability across the globe, impacting up to 70% of the adult population with 6.9 million people affected in Australia in 2014-2015. Likely to develop mental health conditions and creating a major annual economic burden worldwide, a call for global action was announced to meet the associated challenges for low back pain in 2018. The intervertebral disc (IVD) herniation, a major cause for IVD degeneration and low back pain, is manifested by structural defects leading to the disruption of the outer covering layers of the IVD (annulus) and leakage of the inside soft material (nucleus) through the annuls. The IVD herniation resulted in approximately 15 million physician visits with an economic impact exceeding $50 billion in the US, annually. Despite intense research interest, proposed repair strategies to replace the nucleus and seal the annulus structural defects after IVD herniation has failed, and no regeneration policy has translated into meaningful clinical practice. The only available approach, which is still undergoing large clinical trials, is a metal-base implant that targets to stop the reoccurrence of herniation. The implant lacks regeneration capability and fails to maintain native IVD tissue structure and associated mechanical function. Research Challenge: Recent researches on the development of suitable injectable implant for IVD regeneration have failed, since the materials itself often suffered low adhesion, inappropriate mechanical strength, cytotoxicity and poor performance in the biological environment. Research Specific Question: How to engineer injectable hydrogels, making them suitable for IVD repair and regeneration? Multidisciplinary Aspects: Understanding the mechanisms of IVD degeneration to stop or reverse this process, or re-establishing function through therapies is a challenge at the multidisciplinary intersection of biomaterials, biomechanics, and cell biology. A combination of the proposed team and their knowledge in tissue engineering and regeneration medicines, IVD’s structure-properties, biomaterials, will arrange a unique research environment to address the gaps in the field. Potential Applications and Benefits: With novel features being: 1- Being injectable and fast cured suitable for a minimally invasive approach to repair the herniated site at the ruptured annulus; 2- It induces regeneration of the IVD tissue; 3- Prevents re-herniation under conditions resembling loads during daily activities; and 4- Restores IVD mechanics at the posterolateral region of the IVD where herniation usually occurs, this research project will engineer the next-generation of the sealant to address the strong need for new therapies in IVD herniation to treat low back pain. It is expected that the project develops an intellectual property that will help create a commercialized implant and create collaborations essential for future grant applications. Aims: To this end, within the time frame of three years, the specific aims of this project are: Aim1: To develop an injectable silk-based biomaterial incorporating synthetic polymers with optimal physical and mechanical properties. Aim2: To render the bioactivity and regeneration properties of the biomaterial. Aim3: To explore the in vivo behavior of the implant in the IVD of an animal (sheep) model. Realistic Modelling of Spinal Cord Injury (SCI) Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor Joanne Tipper Duration: 3 years (possible 6-month extension) School: School of Biomedical Engineering Centre: Centre for Health Technologies Closing date: when filled Domestic and International applications accepted. Traumatic SCI arises from a complex spectrum of conditions which are reflected by idealised representations of axial compression or distraction, dislocation and contusion with only the latter being modelled frequently in research. This lack of clinical and biomechanical relevance has been highlighted by recent research which has demonstrated the important role the biomechanical impact has on defining the subsequent pathophysiological cascade. Tissue engineered models of the SC provide a highly controlled environment with which to carefully interrogate the links between the injury inducing insult, cellular responses and mitigation strategies against cell death or dysfunction. Taking these issues into consideration there is a need to develop models that reflect the broader clinical spectrum of injury scenarios, allow interrogation of the behavioural response to trauma and reduce the need for animal involvement due to ethical considerations and the difficulty of translation. Building on a previous PhD project that utilised astroglial cells embedded in a 3D collagen gel system, coupled with a commercially available impactor, this project will investigate more complex models (incorporating additional cell types e.g. neurons, OPCs) together with alternative materials e.g. bioprinted synthetic hydrogels and different injury scenarios (dislocation, distractions as well as contusion). Stem cell-derived extracellular vesicles for treating osteoarthritis Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Jiao Jiao Li Duration: 3 years (possible 6-month extension) School: School of Biomedical Engineering Closing date: when filled Domestic and International applications accepted. Osteoarthritis (OA) is a leading cause of chronic disability, frailty and unhealthy ageing. It affects patients across a wide age spectrum, from young athletes with injured joints (50% develop OA within 5–15 years of injury) to elderly individuals (over 50% have OA above 55–80 years of age). It is the most common musculoskeletal reason for hospitalisation (33%) in Australia. OA-related pain and disability accelerate the transition to ageing and bring a host of deleterious consequences, including increased mortality risk from cardiovascular disease, diabetes, obesity, and cognitive disorders. The consequences of having OA are therefore much more than limited mobility and drastic decline in quality of life, which are individually and societally catastrophic, but also a substantially increased risk of premature death due to other co-morbidities. OA has no cure. Non-operative treatments are typically prescribed for pain relief, until the symptoms become so severe that a total joint replacement needs to be performed. However, this surgery is associated with increased risks of complications and limited implant lifetime of approximately 20 years. A new therapy that can provide a cure is urgently needed. This project will develop an innovative therapeutic pathway for treating OA – extracellular vesicles (EVs) derived from stem cells. We will optimise the conditions for culturing MSCs, to generate the most effective EVs for OA disease modification. The optimised EVs will be tested in a validated in vivo mouse model for their therapeutic effects on experimentally-induced OA. Proteomic and genomic analyses will be conducted on the optimised EVs to give mechanistic insights into their therapeutic effects. This project is a multidisciplinary collaboration that will establish an innovative pathway for the development of new therapeutics for treating disease, which can be applied not only for OA but also for other diseases. The project outcomes will lead to significant advancements in regenerative medicine, and has potential to benefit hundreds of millions of OA patients worldwide. Location: School of Biomedical Engineering and Kolling Institute, University of Sydney Full multidisciplinary supervision team: Dr Jiao Jiao Li (main supervisor), Professor Gyorgy Hutvagner (proteomics/genomics, nanomedicine), Professor Christopher Little, University of Sydney (osteoarthritis) and Dr Elham Hosseini-Beheshti, University of Sydney (extracellular vesicles). siRNA therapy for triple negative breast cancer via engineered lipid nanoparticles Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Wei Deng Duration: 3 years (possible 6-month extension) School: School of Biomedical Engineering Closing date: when filled Domestic and International applications accepted. Triple negative breast cancer (TNBC) encompasses 15% of breast cancers and poses significant challenges in treatment. Unlike other subtypes of breast cancer that can be treated with hormonal therapy medicines or medicines that target human epidermal growth factor receptor 2 (HER2) protein, TNBC does not respond to these therapies due to a lack of hormone or HER2 receptors. This leaves the clinician with no other targeted therapy options. Therefore, the availability of a new targeted therapy that can combat TNBC with no toxicity and reduced side effects will be of extraordinary benefit to a significant number of TNBC patients. The central hypothesis proposed in this PhD project was that the targeted delivery of siRNA therapeutics to TNBC cells using targeted lipid nanoparticles will eradicate the disease without harming healthy tissues. We will establish a new approach to package and specifically deliver siRNA cargo to TNBC, without harming healthy tissues. We will also perform critical preclinical experiments using our clinically relevant animal models and generate new knowledge on the therapeutic efficacy of siRNA via targeted lipid nanoparticles against TNBC. The PhD students involved in this project will receive training in lipid nanoparticle synthesis and characterisation, cell culture in vitro and bioassay protocols applied in gene technologies. They will be also exposed to components of medical translation. They will work with a multidisciplinary team including senior academics and postdoctoral researchers. The ideal candidate should have lab training experience in areas such as chemistry, biotechnology, or materials science. Civil and Environmental Engineering Contribution of Comammox Process to Sustainable Wastewater Treatment Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Bruce Ni; bingjie.ni@uts.edu.au Duration: 3 years (possible 6 month extension) School: Civil and Environmental Engineering Centre: Centre of Technology in Water and Wastewater Closing date: when filled Domestic and International applications accepted. This project aims to understand the versatility, activity and physiological features of comammox bacteria, the newly-discovered complete nitrifiers, in Australian wastewater treatment systems, and to model and evaluate their contributions to biological nitrogen removal process. Nitrogen transformations are crucial microbial processes in the wastewater treatment ecosystems, with nitrification largely responsible for ammonium oxidation but comammox previously overlooked. The expected outcomes will develop new knowledge on the comammox process and provide novel insight and technological solution to refine strategies to manipulate nitrification processes for achieving improved biological nitrogen removal and sustainable wastewater management. Computational mechanics and design optimisation for energy absorption of materials under impact loads Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Dr Jianguang Fang Duration: 3 years (possible 6 month extension) School: Civil and Environmental Engineering Closing date: when filled Domestic and International applications accepted. The project “Machine learning-based design of triply periodic minimal surface structures” is calling for applications for PhD scholarship commencing in 2021. This project is funded by the Australian Research Council Discovery Early Career Researcher Award. Candidates with knowledge and research experience in computational mechanics, design optimisation and machine learning are encouraged to apply. This project aims to develop a new approach to design of new lightweight, crashworthy and manufacturable structures by taking advantage of the latest technologies in computational optimisation, artificial intelligence and additive manufacturing. The study intends to develop a new machine learning-based multiscale design framework to seek optimal materials and structures, considering fabrication-induced defects and uncertainty. The expected outcome of this project is new methodologies for generating eco-friendly structures with robust mechanical properties in crashing applications. This should provide significant benefits to transport industries by enhancing structural safety and energy saving for next generation vehicles. Who is Eligible Master Degree by research or Bachelor Degree with strong academic record which is equivalent to First -Class Honours Major: Mechanics, or Mechanical, or Civil Engineering Domestic students or international students (meeting UTS English Proficiency requirement) currently residing in Australia. Selection Criteria Demonstrated self-motivation and commitment to work on research topics. Demonstrated experience in undertaking research in the fields of computational mechanics, design optimisation and machine learning. Excellent written skills evidenced by scientific journal papers, conference papers, or technical reports. Excellent interpersonal and oral communication skills Other Information Applicants must meet the eligibility and address all the selection criteria. In addition to the above eligibility criteria for the scholarship, students should meet the UTS admission requirements to UTS PhD program. The minimum eligibility requirements for admission are available at https://www.uts.edu.au/future-students/postgraduate/essential-info/admission-requirements. How to Apply In the first instance, interested applicants should send their CV, brief (maximum one page) supporting statement, 3 referees and publications (if applicable) to Dr Jianguang Fang at Jianguang.Fang@uts.edu.au and following the initial endorsement by the supervisor, applicants will go through the UTS online application process. Decarbonising built environments with hempcrete and green wall technology Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Prof Arnaud Castel Duration: 3 years (possible 6 month extension) School: Civil and Environmental Engineering Closing date: when filled Domestic applications only. This project aims to develop an integrated prefabricated building panel solution combining green wall and hempcrete technology to address environmental problems associated with the usage of carbon intensive construction materials, dense urbanisation, climate change and biodiversity. Innovation in hempcrete technology consist in using low carbon options including alkali-activated binders and biomineralization technology, glass waste replacing natural sand. Hempcrete green wall panels will be design to be carbon positive, improve the thermal performance of buildings, provide better acoustic insolation, reduce the risk of mould proliferation, control indoor humidity and air quality and improve indoor thermal comfort. Controllable synthesis of multifunctional boron-based 2D materials (PhD scholarship funded by ARC Future Fellowship) Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Up to $15,000 top-up per annum is available for outstanding candidates. Contact: Dr Zhenguo Huang Duration: 3 years (possible 6 month extension) School: Civil and Environmental Engineering Centre: Centre of Technology in Water and Wastewater Closing date: when filled Domestic and International applications accepted. The project “Controllable synthesis of multifunctional boron-based 2D materials” is calling for applications for PhD scholarship commencing in 2021. This project is funded by the Australian Research Council’s Future Fellowship. Candidates with knowledge and research experience in wet chemistry and materials chemistry are encouraged to apply. This project aims to make it possible to control the synthesis of boron-based two-dimensional (2D) materials with the desired following features in single or multiple aspects: thickness, composition, lateral sizes, porosity, surface area, and functionality. It intends to do so by designing and synthesising novel precursors, and by optimising the fabrication process of boron-based 2D nanosheets for different applications. The project will advance our fundamental knowledge in synthetic chemistry, materials chemistry, materials engineering and physics. It is expected to take us closer to unlocking the potential of boron- based 2D materials for real-world applications in, for example, energy storage and high-performance flexible electronics. Eligibility Criteria Master Degree by research or Bachelor Degree with strong academic record which is equivalent to First -Class Honours Major: Chemistry, or Materials Science, or Chemical Engineering Domestic students or international students (meeting UTS English Proficiency requirement) currently residing in Australia. Selection Criteria Demonstrated self-motivation and commitment to work on research topics. Demonstrated experience in undertaking research in the fields of chemistry, materials science, or chemical engineering Excellent written skills evidenced by scientific journal papers, conference papers, or technical reports. Excellent interpersonal and oral communication skills Ability and capacity to implement required health and safety policies and procedures How to apply Applicants must meet the eligibility and address all the selection criteria. In addition to the above eligibility criteria for the scholarship, students should meet the UTS admission requirements to UTS PhD program. The minimum eligibility requirements for admission are available at https://www.uts.edu.au/future-students/postgraduate/essential-info/admission-requirements. Candidates must lodge their applications by email (including a full transcript of results of all subjects studied) to A/Prof. Zhenguo Huang via email: Zhenguo.huang@uts.edu.au. Enhancing anaerobic digestion using a novel technology (ARC Discovery Project funded PhD scholarship) Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt) Fee waivers may also be considered for the successful candidate. Contact: Dr Qilin Wang Duration: 3 years (possible 6 month extension) School: Civil and Environmental Engineering Centre: Centre of Technology in Water and Wastewater Closing date: when filled Domestic and International applications accepted. Wastewater treatment is producing large amounts of sludge, which represents a largely untapped energy source. This project aims to develop and demonstrate an innovative, economically attractive and environmentally friendly technology to enhance anaerobic sludge digestion. The PhD candidate is expected to have good biological wastewater and sludge treatment background. The successful candidate will receive systematic training in biological wastewater treatment processes, reactor technology and sludge anaerobic digestion. The student will conduct detailed laboratory scale investigations and fundamental investigations. The candidate will be housed in an excellent research environment with excellent laboratory facilities and expertise. The successful candidate must have a four-year bachelor degree with Honours class I or IIA, or Master's degree in environment engineering, chemical engineering, biotechnology or related areas and have interest in water and wastewater technologies. Maximising bioenergy recovery from sewage sludge Scholarship: This project includes funding for two living stipend scholarships at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidates. The scholarships are funded by a new ARC Discovery grant Contact: Dr Qilin Wang Duration: 3 years (possible 6-month extension) School: Civil and Environmental Engineering Centre: Centre of Technology in Water and Wastewater Closing date: when filled Domestic and International applications accepted. Maximising Bioenergy Recovery from Sewage Sludge. Sewage treatment is producing large amounts of sewage sludge, which represents a substantial, but largely untapped, energy source. This project aims to develop and demonstrate an innovative, economically attractive and environmentally friendly technology, and the underpinning science, to maximise bioenergy recovery from sewage sludge. This project is expected to benefit Australia by substantially reducing the reliance on fossil fuels and accelerating a shift to affordable renewable energy. The outcomes of the project would provide significant energy, economic, environmental and social benefits for Australians. The successful candidate will receive systematic training in biological wastewater treatment processes, reactor technology and sludge anaerobic digestion. The student will conduct detailed laboratory scale investigations and fundamental investigations. The candidate will be housed in an excellent research environment with excellent laboratory facilities and expertise. The successful candidate must have a four-year bachelor degree with Honours class I or IIA, or Master's degree in environment engineering, chemical engineering, biotechnology or related areas and have interest in water and wastewater technologies. Multiscale modelling of fluid-particle transport in porous media Scholarship: This project includes funding for two living stipend scholarships at the Research Training Program rate of $28,854 per annum (tax-exempt). Fee waivers may also be considered for the successful candidates. Contact: Xuzhen He Duration: 3 years (possible 6 month extension) School: Civil and Environmental Engineering Closing date: when filled Domestic and International applications accepted. Dr Xuzhen is seeking a high-achieving PhD student in 2022. The research project is “Multiscale modelling of fluid–particle transport in porous media”, which is funded by the Australian Research Council Discovery Early Career Researcher Award. Candidates with knowledge and research experience in computational fluid mechanics, discrete element method, and/or multiscale modelling (homogenisation theory, statistical mechanics) are encouraged to apply. About the project: The aim of this project is to use a multiscale approach to rigorously model fluid–particle transport in porous media – a fundamental process in many engineering problems. With advanced parallel-computing tools, a microscale model is developed to incorporate interacting grains, water, and particles. The model and innovative upscaling methods will transform our understanding of mechanisms and allow development of predictive models for particle transport in both steady and unsteady porous flows. The fundamental knowledge and new-generation numerical models will support technological advances to directly benefit rail and road construction and their maintenance, fuel and renewable-energy extraction, coastal soil and water protection, and bushfire control. Dr Xuzhen is a Lecturer and ARC DECRA Fellow at UTS. He obtained his bachelor’s degree from Tsinghua University and studied in the University of Cambridge for his PhD. In 2015, he received the prestigious John Winbolt Prize from Cambridge. About the role: The PhD candidate is expected to meet following criteria: • Master’s degree by research or bachelor’s degree with a strong academic record which is equivalent to first-class honours • Domestic students or international students (meeting UTS English Proficiency requirement) currently residing in Australia (preferred) • Demonstrated self-motivation and commitment to work on research topics. • Demonstrated experience in undertaking research in the fields of computational fluid mechanics, discrete element method, and/or multiscale modelling. • Demonstrated programming skills (C/C++/CUDA preferred). • Excellent written skills evidenced by scientific journal papers, conference papers, or technical reports. • Excellent interpersonal and oral communication skills Osmotically driven membrane processes for power generation and water purification Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt) Fee waivers may also be considered for the successful candidate. Contact: Dr Ali Altaee Duration: 3 years (possible 6 month extension) School: Civil and Environmental Engineering Centre: Centre of Technology in Water and Wastewater Closing date: when filled Domestic and International applications accepted. The UTS Centre of Technology in Water and Wastewater (CTWW) is looking for an enthusiastic local or international PhD candidate to participate, under the supervision of Dr Ali Altaee, in a research project on osmotically driven membrane processes. The PhD program includes theoretical and laboratory work on cutting-edge technologies of renewable energy and water purification. Candidates with knowledge in membrane technology and energy efficiency, and who also have previous publications, are highly encouraged to apply. Knowledge in computer programming software would also be highly appreciated and desirable. The successful candidate may need to travel to Europe as part of the PhD research program. This project is a great opportunity for the successful applicant to learn new skills and to gain hands-on experience in the Energy-Water nexus. Interested candidate should contact Dr Ali Altaee directly. Overcoming microplastics induced inhibition on waste-to-energy conversion Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Bruce Ni; bingjie.ni@uts.edu.au Duration: 3 years (possible 6 month extension) School: Civil and Environmental Engineering Centre: Centre of Technology in Water and Wastewater Closing date: when filled Domestic and International applications accepted. This project aims to develop an innovative technology and the underpinning science to achieve stable and efficient mitigation of emerging microplastics induced inhibition that is becoming a key barrier hindering waste-to-energy conversion in anaerobic digestion. Anaerobic digestion is a low-cost technology widely used to divert sewage sludge to renewable energy production. However, the increasing levels of microplastics captured in sludge leads to low methane yield and process failure due to their small size and specific characteristics. The outcome of the project will remove the emerging barrier to enhance energy recovery that can be applied in existing anaerobic digestion infrastructure for addressing Australia’s increasing energy demand. Computer Science AI-based Approaches for Augmenting/Modelling Human Performance Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt) Fee waivers may also be considered for the successful candidate. Contact: Dr YK Wang Duration: 3 years (possible 6-month extension) School: School of Computer Science Centre: Centre for Artificial Intelligence (CAI) Closing date: when filled Domestic and International applications accepted. Artificial Intelligence (AI) changes our world a lot in recent years. AI-based approaches benefit the most powerful and convenient services. Meanwhile, Virtual Reality (VR) and/or Augmented Reality (AR) is a new interactive technology. All technologies aim to make our life easier. However, one interesting question is how we can wisely use these technologies to augment human performance. In this project, we aim to leverage AI, state-of-the-art biosignal sensors, VR and/or AR technology to bring new insights or concepts for human performance modelling into a future life. Therefore, the students who have high interests in AI, VR, AR, data analytics, or biosignal processing are highly welcome to apply. Selection Criteria: 1. Interests in Data Analytics, Artificial Intelligence (AI), Virtual Reality (VR), Augmented Reality (AR), and/or biosignal processing 2. Very STRONG programming skills in Python, Matlab and Unity 3D AI-based Program Analysis to Pinpoint Emerging Software Vulnerabilities Scholarship: This project includes funding for a living stipend scholarship at the rate of $38,000 per annum (tax-exempt). Contact: Dr Yulei Sui Duration: 3 years (possible 6-month extension) School: School of Computer Science Centre: Centre for Artificial Intelligence Closing date: when filled Domestic applications only. The ideal candidate will be based in CAI to conduct her/his research in topic “Learning to Pinpoint Emerging Software Vulnerabilities”. The project aims to develop new foundational machine learning techniques to pinpoint vulnerabilities in modern software codebases. The candidate will be supervised under Dr. Yulei Sui. The student will work in a vibrant research team consisting of a number of PhD students to quickly get into this new and exciting research area. The stipend of the scholarship is $28,092 per annum (tax-exempt) for 3.5 years, plus a top-up scholarship. The qualified candidate will also receive a tuition-fee waiver. We are looking for self-motivated candidates who meet the following requirements: a bachelor's or master's degree in the area of Computer Science or related discipline; evidence of research ability - e.g. an honours thesis, a minor thesis, publication(s), and a preliminary research proposal, developed under the guidance of the supervisor; programming skills in one of C/C++, Java and Python. AI-based Software Security Analysis Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt) Fee waivers may also be considered for the successful candidate. Contact: Dr Yulei Sui Duration: 3 years (possible 6-month extension) School: School of Computer Science Closing date: when filled Domestic and International applications accepted. The project aims to develop new foundational machine learning techniques to improve existing software security techniques and to understand and visualize software activities. The student will work in a vibrant research team consisting of postdocs and a number of PhD students to quickly get into this new and exciting research area. The stipend of the scholarship is $28,597 per annum (tax-exempt), plus travel funds for attending conferences. The qualified candidate will also receive a tuition fee waiver. We are looking for self-motivated candidates who meet the following requirements: - a bachelor's or master's degree in the area of Computer Science or related discipline; - evidence of research ability - e.g. an honours thesis, a minor thesis, publication(s), and a preliminary research - proposal, developed under the guidance of the supervisor; - programming skills in one of C/C++, Java and Python. Artificial Intelligence for Multi-Modal Traffic Management Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Dr Simona Mihaita Duration: 3 years (possible 6-months extension) School: School of Computer Science Centre: Data Science Institute Closing date: when filled Domestic and International applications accepted. Managing traffic represent a true challenge for all traffic centres around the world, especially under an ever growing urban population living in cities. The increased traffic congestion is linked to an increased data availability from transport modes in the city, whether is regular or public transport, shared or on-demand services, electric scooters, etc. This PhD project aims to study and apply various Artificial Intelligence algorithms and build a smart modelling framework that would help manage traffic across all available modes in a city, under both regular and disrupted traffic conditions (incidents/public events/travel restrictions due to pandemics, etc.). This implies a combination of multidisciplinary research from computer science and transport modelling. The first part of the PhD will focus on conducting an intensive state-of-art on the usage of AI techniques for managing transport across the globe, followed by the construction of a modelling framework on a real-city study. This will be alimented by the best performing machine and deep learning models to predict traffic congestion and travel patterns across all travel modes in advance. While recurrent traffic modelling back-up by AI can provide good insights on traffic patterns, incidents/public events or temporary travel restrictions are stochastic events which have unique features changing dynamically in time. The second part of this project will aim at extending the modelling framework for early anomaly detection across all transport modes which can help to release early traffic alarms to operators for taking action. The last part of the PhD will consist in consolidating results and writing up the PhD thesis. Some examples of previous works on this topic can be found in [1]-[5]. Funding: The PhD student will be located within the Future Mobility Lab at UTS (www.fmlab.org) under the supervision of Dr. Simona Mihaita. This work is funded under the ARC Linkage Project LP180100114, a joint collaboration between UTS, Data61, Swinburne University of Technology and 2 major universities in Singapore: NUS (National University of Singapore) and NTU (National technology University of Singapore). Regular meet-ups and workshops will be organising for presenting new findings and learn from new techniques applied both in Australia and Singapore. Domestic students are highly encouraged to apply – deadline 30th of May for Enrollment in Spring 2020. Deadline for international students: 30th of June 2020 for enrolment in Autumn 2021. The candidate: Interested candidates must have solid background knowledge in computer science – machine and deep learning/data science and desirably transport modelling. Experience with handling large and complex data sets and strong PyThon programming skills are a big plus. We are looking for a candidate with a master by research qualification and demonstrated research capabilities (preferably through publications). Candidates with publications in major conferences/journals will be prioritised. The position will be open until the ideal candidate is identified. For more details, please contact: adriana-simona.mihaita@uts.edu.au BIBLIO: Mihaita, A.S., Li Haowen, He Zongyang, Rizoiu Marian-Andrei, Motorway Traffic Flow Prediction using Advanced Deep Learning, IEEE Intelligent Transport Systems Conference, Auckland, New Zealand, 27-30 October 2019. Mihaita, A.S., Liu, Z., Cai, C., Rizoiu, M.A “Arterial incident duration prediction using a bi-level framework of extreme gradient-tree boosting”, ITS World Congress 2019, Singapore, 21-25 Oct 2019, Preprint link. Mao, T., Mihaita, A.S., Cai, C., Traffic Signal Control Optimisation under Severe Incident Conditions using Genetic Algorithm, ITS World Congress 2019, Singapore, 21-25 Oct 2019, Preprint link. Shaffiei, S. Mihaita, A.S., Cai, C., Demand Estimation and Prediction for Short-term Traffic Forecasting in Existence of Non-recurrent Incidents, ITS World Congress 2019, Singapore, 21-25 Oct 2019, Preprint link. Wen Tao, Mihaita A.S., Nguyen Hoang, Cai Chen, Integrated Incident decision support using traffic simulation and data-driven models. Transportation Research Board 97th Annual Meeting (TRB 2018), Washington D.C., January 7-11, 2018, H5=48. Preprint link. Autonomous machine learning for decision making (ARC Laureate project) Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Distinguished Professor Jie Lu Duration: 3 years (possible 6-month extension) School: School of Computer Science Centre: Centre for Artificial Intelligence Closing date: when filled Domestic and International applications accepted. An opportunity presents for an enthusiastic and talented recent graduate to be part of an ARC Laureate project. The project aims to create a novel research direction – autonomous machine learning for data-driven decision making– that innovatively and effectively learns from big data to support decision-making in complex (massive, uncertain, dynamic) situations. A set of new theories, methodologies and algorithms will give artificial intelligence the ability to learn autonomously from data to enable machine learning capability to effectively handle tremendous uncertainties in data, learning processes and decision outputs, particularly enabling smart learning in massive domains, massive streams, and massive-agent sequentially changing environments. The project’s outcomes are expected to improve data-driven decision-making in multiple industry sectors. The successful candidate is likely to: Have a master’s degree from a recognised university in a relevant discipline (such as Computer science, mathematics, statistics or joint mathematics and computing, or related areas) Fulfil UTS Doctor of Philosophy (PhD) admission criteria, including English language requirements A strong curiosity to learn and apply machine learning techniques into decision making Familiarity with machine learning and decision-making techniques such as transfer learning, optimisation, classification, regression, neural networks, and decision support systems, Solid skills of Python or other programming languages Excellent data analytical and modelling skills Good English written and verbal communication skills Biotremological communication channels of biogenic, multi-functional materials Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Dr Sebastian Oberst Duration: 3 years (possible 6 month extension) School: School of Computer Science and School of Mechanical and Mechatronic Engineering Centre: Centre of Audio, Acoustics and Vibration Closing date: when filled Domestic and International applications accepted. Termites live in colonies of several million individuals, underground and in the dark. The substrate termites feed and live on is biogenically designed or modified to serve as a multifunctional, multi-scale material. Termites use this substrate to efficiently ventilate and air-condition their nest, to carry a maximum of load by using a minimal materials, as food storage, nursery or for defence of the colony and as communication channel. Yet, almost no details of how these different functions are achieved, are known. This project interfaces Mathematics/Computer science with Engineering to engage pattern recognition and machine learning tools to understand the combined effects of the communication channel as multifunctional structure with various signalling types (walking, foraging, alarming). The goal is to transition the findings into the design of novel, topologically optimised signal filters, leading to engineered highly efficient, lightweight multiscale metamaterials for the construction and manufacturing industry. The potential candidate should be self-driven and motivated, should have an Australian PR or citizenship, and a university degree in Engineering, Physics or Mathematics or comparable discipline. Any other project info (e.g. top ups, sponsor info): ARC Discovery Project, FEIT. Brain Robot Interface for Physical Human Robot Collaboration Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Professor CT Lin Duration: 3 years (possible 6 month extension) School: School of Computer Science and School of Mechanical and Mechatronic Engineering Centre: Centre of Audio, Acoustics and Vibration Closing date: when filled Domestic applications only ntuitive and timely conveying of a user’s intention to a robot offers potential to improve the efficiency and operational compliance of physical human robot collaboration (pHRC) in complex and unstructured environments. In pHRC the robot is expected to follow the human’s intended motion during the continuous movement of human and robot. It is now possible to exploit machine learning to calibrate a robot to meet a user’s intention. Cognitive conflict, which is induced in brain automation control by perceiving the deviations in robot action from the user’s intended action, can reliably indicate the user’s intentions. However, this critical factor in pHRC is not yet well understood. This project addresses two major gaps in the knowledge needed to significantly improve the performance and user experience in pHRCs. Building a quantum computing benchmarking and analytics platform Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. You will also be encouraged to apply for Sydney Quantum Academy top-up scholarships. This would include the stipend to be $35,000 per annum and increase the PhD duration to 4 years. You will also become a member of this academy. Contacts: Dr Simon Devitt Duration: 3 years (possible 6-month extension) School/Centre: School of Computer Science Centre: Centre for Quantum Software and Information Closing date: when filled Domestic applications only. In September 2019, the quantum computing group at Google AI published a paper in the journal Nature. “Quantum supremacy using a programmable superconducting processor.” claimed, for the first time, that a universally programmable quantum computer, built using superconducting quantum-bits (qubits), was now good enough to perform a computation in 200 seconds that would take the best supercomputer in the world 10,000 years. While there has been significant discussion surrounding the specifics of the Google result, one consensus emerged that was noted in paragraph two of the paper: “Quantum supremacy also heralds the era of Noisy Intermediate- Scale Quantum (NISQ) technologies.” NISQ era quantum computing essentially packages up the observation that quantum computers containing 10’s or 100’s of millions of qubits are not going to exist in the short term, hence quantum computing scientists need to find something that we can do - with either scientific or commercial impact beyond the existence of the machine itself - to sustain R&D long enough to achieve large-scale quantum computing, where impactful algorithms related to quantum simulation, cryptography, optimization and machine learning definitely do exist. While there is a significant amount of excellent work throughout the quantum community related to algorithm development, analysis, optimisation and implementation, the sudden push of quantum computing out from the academic sector and into the commercial sector have created a mismatch related to claims regarding what these machines can do and what is actually backed up by solid theoretical and/or experimental work. This has caused an extensive amount of confusion that is beginning to hamstring real development of both experimental quantum computing systems and theoretical work related to when and if quantum computers can provide a real benefit to a specific problem or set of problems. In the classical world, the field of computer benchmarking was designed to help assess both the hardware and software aspects of computing. This could be to confirm that hardware clock speeds are consistent with what is advertised in a newly designed microprocessor or it could be that a computer program is subject to a series of programs or operations to test that it is either free of bugs, or performs to a level that is expected by either the developer or a potential client. These areas of classical computer science are essentially non-existent in the quantum world. In the vast majority of cases, hardware and software performance is defined by the groups that have a vested interest in promoting the superiority of their approaches or technology. This is particularly true for quantum software and algorithm development, where a large fraction of results don’t even bother to justify the need for using a quantum computer for their particular algorithm in the first place. Since 2016 we have been working on potential solutions to this problem and have been developing an initial structural framework to a subfield that we have dubbed Quantum Resource Estimation and performance analytics. This framework sits between the quantum software community and the quantum hardware community and acts to link together these two, somewhat disparate, areas of research, providing continuity that will allow software researchers to quantify and optimise the hardware requirements of their programs, and allowing quantum hardware developers to understand the micro-architectural structures needed for high-impact applications. We are developing the tools for analysing quantum algorithms in real-world hardware platforms. This project would suit those with knowledge and experience in software development, online service development, quantum information science and computing. Closed-Loop Multimodal System for VR or AR Approaches Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Dr YK Wang Duration: 3 years (possible 6-month extension) School: School of Computer Science Centre: Centre for Artificial Intelligence (CAI) Closing date: when filled Domestic and International applications accepted. Virtual Reality (VR) or Augmented Reality (AR) brings new interactive experience in a real-world environment. However, the user still majorly relies on controllers as the interface. A popular application is the multimodal brain-computer interface (BCI) which integrates multiple physiological patterns to estimate the level of cognitive ability or human intention. BCI research aims to expand our understanding of the cognitive functions underlying human perceptual, cognitive, and motor functioning. Considerable progress has been made in improving the estimation accuracy of BCI using various sensor technologies, there is a new direction to leverage multimodal BCI for developing VR- or AR-related approaches that can bring new insights or concepts into future life. Artificial Intelligence (AI) and state-of-the-art data analytics algorithms may be also introduced during the whole project. The students who have high interests in VR, AR, data analytics, AI, or BCI are particularly encouraged to apply. Selection Criteria: 1. Interests in Data Analytics, Artificial Intelligence, Brain-Computer Interface, Virtual Reality, and/or Augmented Reality. 2. VERY STRONG programming skills including C#, C++, Python, Matlab, Unity 3D etc Complex dynamics in biotremology Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). An application for a top up scholarship is possible and fee waivers may also be considered for the successful candidate. Contact: Dr Sebastian Oberst Duration: 3 years (possible 6 month extension) School: School of Computer Science and School of Mechanical and Mechatronic Engineering Centre: Centre of Audio, Acoustics and Vibration Closing date: when filled Domestic and International applications accepted. If you are interested in this project please contact Dr Sebastian Oberst and include your CVtogether with your relevant diploma, transcripts, publication list, contact details of two referees and you motivation letter, If interested please contact sebastian.oberst@uts.edu.au and include your CV and motivation letter Motivation letter and your Curriculum Vitae together with relevant diploma, transcripts, publication list and contact details of two referees. The Centre for Audio, Acoustics and Vibration (CAAV) was formed in 2017 and now has nine full time academic staff. The Centre is based at Tech Lab, which is a brand new research led facility that is close to the airport in Sydney. Tech Lab hosts brand new state-of-the-art acoustics experimental facilities that includes an anechoic chamber, semi-anechoic chamber, reverberation room and sound transmission loss suite. These new facilities will support new research projects in acoustics, including this current project. Termites communicate mainly over vibrations transmitting and receiving miniscule wave packages, which travel along wood fibres and termite-built clays. Our research in the past indicated that it should be possible in principle to use vibration signals to determine an individual ants’ or termites’ location (vibroklinotaxis). We were the first who evidenced termites substitute wood by building load-bearing structures. While past research has been focused either on the sender or the receiver, individual or groups of termites, the properties and the function of the substrate as food, communication channel or building materials has been neglected. The project aims at studying structures of the higher and lower termites. Different structures of within the mound and close to foraging sites are collected from nature reserves (Darwin, Canberra). Mounds of different colonies will be dissected and the material specimen will be taken out, analysed using micro-CT and mass spectroscopy. The static and dynamic material properties need to be experimentally and statistically analysed. The material features will be clustered using machine-learning techniques, 3D recurrence quantification and recurrence networks and matched with geometry. Using a computer model, vibro-acoustic simulations will be conducted to explore the role of transfer paths in vibroklinotaxis. The successful candidate will work in a thriving acoustics research group at a brand new facility dedicated to impactful research and which will include the chance to collaborate with researchers in other areas at Tech Lab, as well as undergo research training and development. Findings are expected to contribute to the understanding how termites build and whether different functions and properties can be assigned to different parts of their structures. Novel bio-inspired acoustic porous materials are likely to be innovated by this research – with huge potential for technology transfer. The successful candidate holds a MSc/MEng degree either in physics, applied mathematics, theoretical mechanics and materials engineering (with an interest to work interdisciplinary). Skills in mathematics, especially statistics and machine learning are required. Knowledge of nonlinear dynamics and nonlinear time series is not expected but desired. Excellent command of English is necessary and communications as well as presentation skills are important. The project is suitable to candidates who have a solid background in experimental vibration testing and transfer path analysis as well as signal processing methods. A potential candidate also requires good knowledge of statistics and numerical modeling and should be interested in working with insects and insect structures. Some travel and fieldwork will be required. Data-Driven Hexahedral Meshing Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Nico Pietroni Duration: 3 years (possible 6-months extension) School: School of Computer Science Closing date: when filled Domestic and International applications accepted. Hexahedral and hex-dominant volumetric meshing of 3D shapes is a well investigated, yet still open, research topic. They seek to generate meshes with well-shaped, or box-like, elements whose outer surface closely aligns with that of the input model. Despite multiple attempts, quality all-hex meshing remains elusive, and industrial models are still meshed using semi-manual block decomposition, a tedious and time-consuming process. Existing automatic methods for quality all-hex meshing are applicable to only a subset of inputs; while more general purposes produce inferior quality meshes or fail to capture surface features. In this project, we propose a new approach that exploits a data-driven model to create volumetric meshes composed by hexahedral elements using a philosophy similar to data-driven interactive quadrangulation (see https://www.youtube.com/watch?v=H8K5CyQB_kc&feature=emb_logo). Data Innovation for Zero Carbon Buildings Scholarship: This project includes funding for a living stipend scholarship at the rate of $38,000 per annum (tax-exempt) and a Topup of $3,000 per annum (tax-exempt), for the candidate, for items such as a computer, publishing fees, travel or conference costs. Fee waivers may also be considered for the successful candidate. Contact: Hongda Tian Duration: 3 years (possible 6-months extension) School: School of Computer Science Closing date: 12 November 2021 Domestic and International applications, who are onshore and have a valid visa, accepted. We encourage female identifying and Indigenous applicants to apply. Short description According to the IEA, for the international community to meet the goals of the Paris Agreement, by 2030 all new buildings will need to be ‘zero-carbon ready’ and one fifth of all existing buildings (incl. most institutional real estate) will need to be retrofitted to zero-carbon ready levels. Zero-carbon-ready buildings are essential because they will support the massive growth in renewable energy generation that is required. Flexible demand from buildings will underpin the economic case for the infrastructure investment required to decarbonise the global energy supply system. The scholarship will support research in data science and machine learning, with a focus on commercial building demand forecasting and load optimisation in a dynamic operating environment with potentially conflicting environmental, cost and health objectives. Building owners, occupiers, network operators and electricity retailers all stand to benefit greatly if this ‘built in system capacity’ can be better understood and actively addressed. Project description The PhD project will be completed in the School of Computer Science and is funded by a generous 3-year scholarship by the RACE for 2030 Collaborative Research Centre in collaboration with industry partner Buildings Alive Pty Limited. This PhD project will explore data-driven software solutions that will support the integration of buildings with the supply system as ‘network assets’ that can operate ‘carbon free 24/7’. Large commercial, residential and institutional buildings have significant energy storage potential which may be addressed at scale to both increase demand on electricity networks during times of low demand (and low wholesale price and low carbon intensity) and add capacity during times of high demand (and high price and high carbon intensity). This ‘active efficiency’ opportunity is poorly understood by policy makers, planners and building practitioners. There are significant gaps in the literature and there have been very few field studies. Building owners, occupiers, network operators and electricity retailers all stand to benefit greatly if this ‘built in system capacity’ can be better understood and actively addressed by applying emerging data science technology and techniques. The research will leverage contemporary machine learning and data science approaches and draw upon a large (and constantly updating) database of meter, weather and IoT data from hundreds of commercial and institutional buildings across Australia and internationally. The research will explore how the application of data science and data innovation can deliver real-world energy and carbon impacts for Australian business. This PhD will be completed through a PhD by publication/compilation or thesis with a minimum of three peer reviewed publications and will commence with an industry focused Rapid Review. This PhD will also be supported by an Industry Reference Group throughout the project providing the opportunity to develop advanced research skills, contribute to an important global issue and engage meaningfully with industry. Eligibility Applicants should have a First-Class Honours or Master’s Degree or equivalent in a related discipline (e.g. computer science or data science), OR a combination of an upper second-class Honour’s degree or equivalent in a related discipline together with significant full-time professional work experience in a relevant field. Applicants must be eligible for enrolment in their chosen course at Data Science Institute, University of Technology Sydney. It is recommended that students obtain relevant postgraduate information from the relevant university before pursuing a scholarship inquiry. Applicants must be studying full time. Skills and experience In addition to the eligibility criteria, candidates should also have the follow skills and/or experience: Excellent written and verbal communications skills. Demonstrated knowledge in areas directly relevant to machine learning, data science and data engineering Solid skills in the use of modern software languages (e.g. Python/R) and libraries to deliver machine learning, data science and data engineering activities Good time management skills Excellent data analytical and modelling skills You are required to address the following three selection criteria for this position within the body of your one-page cover letter: Experience in the development and deployment of machine learning techniques Experience in data engineering, including data cleaning, data linkage and data interpolation Your interest (and any experience) in delivering applied research in the energy domain You are also encouraged to briefly comment on how you meet the following two additional criteria in your one-page cover letter: Experience working with industry partners, particularly in applied research spaces Your experience in testing algorithms and solutions in real-world environments During the competitive selection process, candidates will also be assessed upon their ability to: Independently pursue their work Collaborate with others, including industry and research partners Analyse and work with complex issues Formulate scientific and industry focused texts Data Science: Frontiers and Algorithms Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contract: Professor Longbing Cao Duration: 3 years (possible 6-month extension) School: School of Computer Science Centre: Advanced Analytics Institute Closing date: when filled Domestic and International applicants accepted. Working with the ARC Future Fellow Prof Cao, theoretical breakthroughs in frontier data science will be built on top of modern statistic and deep learning for complex data, behaviour and systems. Typical issues include learning theories for non-IID big data that is heterogeneous and coupled with complex interactions and relations from attribute values to sources of data. The successful candidates are expected to work on an ARC Future Fellowship (Level 3) project and enterprise data science projects. Interested candidates are expected to: have solid background knowledge in statistics/mathematics, data science and artificial intelligence (in particular statistics, machine learning, data mining and pattern recognition), a master by research qualification in the above areas, demonstrated research capabilities (through publications), candidates are expected to have publications with major conferences/journals, effective written and verbal communications in English. The candidates will work at the Data Science Lab (www.datasciences.org) at UTS Advanced Analytics Institute, an active team with strong research culture and track record in quality and impact-driven research and engagement with many major local and international partners. Successful candidates may have opportunities to work with international leaders in the area. The scholarships are available for both domestic and international talents. Tuition fee waivers may also be considered for international candidates. Deep Interaction Learning in Unlabelled Big Data and Complex Systems Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contract: Professor Longbing Cao Duration: 3 years (possible 6-month extension) School: School of Computer Science Centre: Advanced Analytics Institute and Data Science Institute Closing date: when filled Domestic and International applicants accepted. This Australian Research Council Future Fellowship grant will support PhDs to work with the fellow on developing cutting-edge theories and algorithms for Deep Interaction Learning in Unlabelled Big Data and Complex Systems. Candidates are expected to have demonstrated background and research output in statistics, applied mathematics, machine learning, artificial intelligence, data analytics and relevant areas. More information is available at https://datasciences.org/news/recruiting-talented-and-self-motivated-phd-post-doc-visiting-students-scholars/ Designing and benchmarking quantum secure, authentication networks Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. You will also be encouraged to apply for Sydney Quantum Academy top-up scholarships. This would include the stipend to be $35,000 per annum and increase the PhD duration to 4 years. You will also become a member of this academy. Contacts: Dr Simon Devitt Duration: 3 years (possible 6-month extension) School/Centre: School of Computer Science Centre: Centre for Quantum Software and Information Closing date: when filled Domestic applications only. This project lays the theoretical foundations for global quantum networks, by constructing a framework for the most near-term application of distributed entanglement: quantum secure message authentication. Quantum communication networks will transform the computational and security landscape for humanity. However, they will be infrastructure intensive and can not be built in an ad-hoc manner. By developing the foundations of global quantum networks using diverse hardware platforms such as quantum repeaters and quantum satellites, we will inform policymakers and hardware developers as to the best methodologies to realise adaptive and resource-friendly networks. This will pave the way for the global quantum ecosystem of the 21st century. Students with experience in quantum information science, classical security and/or cryptosystems or classical networking theory would be a plus. Coding experience and the ability to build a framework for an online platform is beneficial. Distributed traffic control for connected and autonomous vehicles in mixed traffic environments Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt) Fee waivers may also be considered for the successful candidate. Contact: Dr Simona Mihaita Duration: 3 years (possible 6-months extension) School: School of Computer Science Centre: Data Science Institute Closing date: when filled Domestic and International applications accepted. In an era of rapid technological changes, connected, electric and autonomous vehicles (CAEVs) seem to be the perfect solution for dealing with challenging problems such as congestion, pollution and space optimisation in urban areas. While significant efforts are put together for dealing with regulations, standard adoption and testing some trial cases, few studies have concentrated on studying the impact of adopting such novel technology and the problems coming along with operating in mixed traffic environments. This PhD project aims at proposing both theoretical and transport modelling techniques in order to build an efficient traffic control mechanism responsible of balancing a shared and on-demand CAEV fleet across various urban areas and maintain a high level of service that would minimise travel time for all vehicles on the road (either autonomous, public transport, taxis, etc.). The underlying operational problem associated with the shared on-demand CAEVs is a sequential stochastic control problem with incoming dynamic requests for rideshare, routing optimisation and electrical recharge constraints. In the first part of this project, the PhD student will develop an agent-based simulation tool (or a micro simulation model) for modelling the CAEV behaviour in a real urban setup and testing multiple assignment strategies [1]-[2]. This would include communication between vehicles and route optimisation for arriving in time at random recharge stations across the city subject to specific recharging constraints. Secondly, the focus will be on developing a controller supervision system that would allow traffic operators to balance the traffic demand and CAEV fleet allocation across large urban areas in order to ease traffic congestion [3]. This would take into consideration a dynamic fleet reconfiguration which would operate under safe navigation conditions [4-5]. The PhD student will be located in the newly formed Future Mobility Lab at UTS cofounded by Dr Simona Mihaita, under a new Data Science Institute led by Professor Fang Chen. The institute counts around 30 staff members with research interests spanning across asset management, transportation, behavioural data science and human dynamics. The Data Science Institute has both strong ties with industry, as well as world-class research, providing the ideal environment for solving real-world problems. Interested candidates must have solid background knowledge in transport modelling, traffic control and mathematical modelling (preferably stochastic optimal control, dynamic routing), and strong programming capabilities in Python/R. Experience with transport modelling at micro and meso levels are a big plus. We are looking for a candidate with a master by research qualification and demonstrated research capabilities (publications). Candidates with publications in major conferences/journals will be prioritised. The position will be open until the ideal candidate is identified. If you are interested, please send the following to Dr Simona Mihaita: your CV, grades transcripts from undergrad and Masters, your research proposal ideas on the topic (max. 2 pages; to be refined with supervisor and final selected candidate). Masters thesis manuscript (if applicable) or any other research thesis; a cover letter (no more than one page), outlining how your profile fits the PhD position; 3 referees (academic or industrial supervisors, co-authors): name, position and email; (if you have one) one of your publications which is most relevant for this position. The selected PhD student will work under the supervision of Dr. Mihaita and interact closely with academics from the Future Transport Mobility Lab and a large industrial partner in Australia. Regular meetups and workshops will be organised for presenting new findings and results. References: 1. Mehdi N., Matthew J. R., Agent based model for dynamic ridesharing, Transportation Research Part C: Emerging Technologies, Volume 64, 2016, pp 117-132, ISSN 0968-090X. 2. Pereira, J.L.F, Rossetti, Rosaldo J.F. , An Integrated Architecture for Autonomous Vehicles Simulation, Proceedings of the 27th Annual ACM Symposium on Applied Computing, SAC 12, 2012, isbn 978-1-4503-0857-1. 3. Michael H., Hani S. Mahmassani, Dynamic autonomous vehicle fleet operations: Optimization-based strategies to assign AVs to immediate traveller demand requests, Transportation Research Part C: Emerging Technologies, Volume 92, 2018, pp 278-297. 4. Mao, T., Mihaita, A.S., Cai, C., Traffic Signal Control Optimisation under Severe Incident Conditions using Genetic Algorithm, ITS World Congress 2019, Singapore, 21-25 Oct 2019, Preprint: https://bit.ly/2ITBCwF 5. Mihaita A.S., Tyler P., Menon A., Wen T., Ou Y., Cai C., Chen F., "An investigation of positioning accuracy transmitted by connected heavy vehicles using DSRC", TRB 96th Annual Meeting, Washington D.C., 2017. Electric Vehicles impact using transport modelling and data science Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Simona Mihaita Centre: Date Science Duration: 3 years (possible 6-months extension) School: School of Computer Science Closing date: when filled Domestic and International applications accepted. Electric Vehicle have started to be more and more adopted in various cities around the globe with the hopes of reducing traffic pollution and provide safe and green travel alternatives. However, their adoption is not straightforward and their impact on the local traffic grid or air pollution is highly underestimated. This PhD aims at studying the impact of EV adoption by using a combination of traffic modelling and data science techniques. The work will include the delivery of an analysis platform/framework that connects robust fine-grained local transport simulation with local energy system modelling to explore the electric vehicle (EV) impacts on road usage and battery charging demand. The platform will enable users to test different EV scenarios and explore the emergent effects of local EV patterns on medium-voltage distribution networks and the consumers they service, both now and into the future. Some of the main objectives of this PhD are: Building a microsimulation modelling in Aimsun for traffic congestion evaluation in an Australian city where traffic data is available, Constructing EV recharge stations in the model and implementing routing towards the recharge stations of regular cars, Testing various scenarios concerning the energy consumption and future evolution based on current/predicted traffic flow patterns, Construct models and algorithms for optimising the location of EV recharge stations. Write the manuscript and present results across several conferences or via journal publications. The PhD student will be located within the Future Mobility Lab at UTS (www.fmlab.org) under the supervision of Dr. Simona Mihaita. Domestic students are highly encouraged to apply. The candidate: Interested candidates must have solid background knowledge in data science – and desirably transport modelling. Experience with handling large and complex data sets and strong PyThon programming skills are a big plus. We are looking for a candidate with a master by research qualification and demonstrated research capabilities (preferably through publications). Candidates with publications in major conferences/journals will be prioritised. The position will be open until the ideal candidate is identified. For more details, please contact: adriana-simona.mihaita@uts.edu.au Embodied interaction design in the context of materialising memories Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor Elise van den Hoven Duration: 3 years (possible 6-month extension) School: School of Computer Science Closing date: when closed Domestic and International applications accepted. The world is digitising at a rapid rate, more and more physical objects and activities have become digital and moved online. For many things this is welcome since digitisation has numerous advantages, but for some we miss the physical embodiment. This project will be part of the Materialising Memories research program, in which we study when physicalisation and embodiment would provide benefits in the context of everyday remembering practices. Innovative concepts are worked out into interactive prototypes that will be evaluated in the real world. A project could focus on some of these iterative design phases, and does not have to include all. Any topic loosely related to Memories (which is very broad, look at some example projects in this magazine: http://www.materialisingmemories.com/new-mm-magazine-out-now/) will do, as the focus of this project is on Materialising and Embodying interaction design in everyday life. The approach is design research using qualitative methodology. Creative proposals, that broaden the Materialising Memories portfolio, are welcome. Materialising Memories is based in three universities and countries: University of Technology Sydney, Eindhoven University of Technology and University of Dundee. This project will take place in Sydney, Australia, but could potentially be in collaboration with one of the other two universities. Genetic programming for big data analytics Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Professor Amir H Gandomi Duration: 3 years (possible 6-month extension) Contact: Professor Amir H Gandomi Duration: 3 years (possible 6-month extension) School: School of Computer Science Centre: Date Science Closing date: when filled Domestic and International applications accepted. University of Technology Sydney – City campus. UTS is #1 young university in Australia in 2019 based on QS and THE ranking. UTS is ranked #29 globally and #1 in Australia for the subject area of Computer Science and Engineering (based on 2019 ARWU rankings) This project is about extending Genetic Programming in order to deal with challenging problems including large scale problems. Several topics are going to be investigated in this project including hybrid approaches, information theory, cloud computing, etc. The researcher needs to code genetic programming during this project. A solid background in computer and data sciences as well as strong programming skill (MatLab/Python/Java). A master degree in computer science, data science, mathematics, AI, engineering, or related field. Basic statistics knowledge and familiar with genetic programming and evolutionary computation topics. Large-scale bibliometric data analytics for business intelligence Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Duration: 3 years (possible 6-month extension) Contact: Yi Zhang School: School of Computer Science Centre: Centre for Artificial Intelligence (CAI) Closing date: when filled Domestic applications only. This project is in line with Dr Yi Zhang's 2019 DECRA project, which is to develop computational models incorporating novel AI/data science techniques (e.g., network analytics and deep learning) with bibliometric data (e.g., scientific text, citations, and authorships) and to apply these novel models for business intelligence. Candidates with a background in computer science, information systems and management, data engineering, or related disciplines are welcome. Research topics could be within the area of information retrieval, network analytics, text analytics (including natural language processing), and other related topics. Improving deep and machine learning using second-order information Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Professor Amir H Gandomi Duration: 3 years (possible 6-month extension) School: School of Computer Science Centre: Date Science Closing date: when filled Domestic and International applications accepted. University of Technology Sydney – City campus. UTS is #1 young university in Australia in 2019 based on QS and THE ranking. Also, UTS is ranked #29 globally and #1 in Australia for the subject area of Computer Science and Engineering (based on 2019 ARWU rankings) This project is about incorporating second-order information into machine learning methods in order to boost the initialization and learning processes. From the machine learning methods in this project, it particularly focuses on deep neural networks. Several topics are going to be investigated in this project including hybrid approaches, big data analytics, graph theory, large scale problems. A solid background in data and computer sciences as well as strong programming skill (MatLab/Python). A master degree in data science, computer science, mathematics, AI, engineering, or related field. Background in statistics and machine learning methods, deep learning in particular. Publications with major conferences and/or journals. Improving deep and machine learning using second-order information Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor Yi Yang Duration: 3 years (possible 6-month extension) School: School of Computer Science Centre: Centre for Artificial Intelligence Closing date: when filled Domestic and International applications accepted. This project aims to construct an intelligent bibliometric system to track and predict technological change and recombination from bibliometric streaming data. This project expects to spearhead a new cross-disciplinary direction of research in both bibliometrics and innovation and technology management. Expected outcomes of this project include an intelligent bibliometric system, a technological change tracking method and a dynamic knowledge mapping and prediction method. This should dramatically assist governments in developing science policy and national strategies, academic researchers in exploring research frontiers, and entrepreneurs in gaining competitive strength through product inventions and upgrades, particularly in SMEs. Any other project info (e.g. top ups, sponsor info): This PhD scholarship will be funded by an ARC DECRA project, with 26,694 AUD annual PhD stipend. We prefer candidates with background in computer science, information systems and management, and related disciplines. Large scale graph and high dimensional data processing Scholarship: This project includes funding for a living stipend scholarship at the rate of $27,609 per annum (tax-exempt). Contact: Dr Ying Zhang Duration: 3 years (possible 6-month extension) School: School of Computer Science Centre: Centre for Artificial Intelligence Closing date: when filled Domestic applications only. Research Fields: Big data analytics including graph and social networks, high dimensional data, spatial database, or new research directions combining Machine Learning and Database techniques. Background required: bachelor or master degree in computer science, mathematics or related disciplines; with good programming skills; Avg. mark above 75/100 for students from Top Universities. Financial supports: ARC Discovery Project that provides living stipends AU$27, 609 per year for three years. English requirements: IELTS 6 overall, and 6 on writing or please check the TOFEL requirements by yourself. Short bio of supervisor: Dr. Ying Zhang is a Professor an ARC future fellow (2017-2021) in the Australia Artificial Intelligence Institute (AAII). He have intensively published research results in top venues such as SIGMOD, SIGIR, VLDB, PODS, ICDE,TKDE, VLDBJ, and TODS. He had received seven ARC grants which are under the National Competitive Grants Programme (NCGP) including one ARC ADP fellowship, one ARC DECRA fellowship, one ARC future fellowship and two ARC discovery projects. Please contact Professor Ying Zhang (http://www.uts.edu.au/staff/ying.zhang) for further information. Natural porous vibro-acoustic media Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt) and a $10,000 top up. Fee waivers may also be considered for the successful candidate. Contact: Dr Sebastian Oberst Duration: 3 years (possible 6 month extension) School: School of Computer Science and School of Mechanical and Mechatronic Engineering Centre: Centre of Audio, Acoustics and Vibration Closing date: when filled Domestic and International applications accepted. If interested please contact Dr Sebastian Oberst and include your CV and motivation letter together with relevant diploma, transcripts, publication list and contact details of two referees. The Centre for Audio, Acoustics and Vibration (CAAV) was formed in 2017 and now has nine full time academic staff. The Centre is based at Tech Lab, which is a brand new research led facility that is close to the airport in Sydney. Tech Lab hosts brand new state-of-the-art acoustics experimental facilities that includes an anechoic chamber, semi-anechoic chamber, reverberation room and sound transmission loss suite. These new facilities will support new research projects in acoustics, including this current project. Termites communicate mainly over vibrations transmitting and receiving miniscule wave packages, which travel along wood fibres and termite-built clays. Our research in the past indicated that it should be possible in principle to use vibration signals to determine an individual ants’ or termites’ location (vibroklinotaxis). We were the first who evidenced termites substitute wood by building load-bearing structures. While past research has been focused either on the sender or the receiver, individual or groups of termites, the properties and the function of the substrate as food, communication channel or building materials has been neglected. The project aims at studying structures of the higher and lower termites. Different structures of within the mound and close to foraging sites are collected from nature reserves (Darwin, Canberra). Mounds of different colonies will be dissected and the material specimen will be taken out, analysed using micro-CT and mass spectroscopy. The static and dynamic material properties need to be experimentally and statistically analysed. The material features will be clustered using machine-learning techniques, 3D recurrence quantification and recurrence networks and matched with geometry. Using a computer model, vibro-acoustic simulations will be conducted to explore the role of transfer paths in vibroklinotaxis. The successful candidate will work in a thriving acoustics research group at a brand new facility dedicated to impactful research and which will include the chance to collaborate with researchers in other areas at Tech Lab, as well as undergo research training and development. Findings are expected to contribute to the understanding how termites build and whether different functions and properties can be assigned to different parts of their structures. Novel bio-inspired acoustic porous materials are likely to be innovated by this research – with huge potential for technology transfer. The successful candidate holds a MSc/MEng degree either in physics, applied mathematics, theoretical mechanics and materials engineering (with an interest to work interdisciplinary). Skills in mathematics, especially statistics and machine learning are required. Knowledge of nonlinear dynamics and nonlinear time series is not expected but desired. Excellent command of English is necessary and communications as well as presentation skills are important. The project is suitable to candidates who have a solid background in experimental vibration testing and transfer path analysis as well as signal processing methods. A potential candidate also requires good knowledge of statistics and numerical modeling and should be interested in working with insects and insect structures. Some travel and fieldwork will be required. Next generation software security analysis Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Dr Yulei Sui Duration: 3 years (possible 6-months extension) School: School of Computer Science Closing date: when filled Domestic and International applications accepted. This project aims to systematically investigate next-generation static program analysis to provide modular and parameterised analysis mechanism by leveraging recent advances in machine learning, while supporting refinement-based precision to effectively detect memory corruption bugs, including spatial memory errors (e.g. buffer overflows) and temporal memory errors (e.g. use-after-frees) for system software (e.g. written in C/C++). Privacy preservation for presonalised smart devices Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt).Fee waivers may also be considered for the successful candidate. Contact: Associate Professor Tianqing Zhu Duration: 3 years (possible 6 month extension) School: Computer Science Centre: Centre for Cyber Security Closing date: when filled Domestic and International applications accepted. Smart devices and the Artificial Intelligence (AI) they contain are significantly improving quality of life for many people. Smart drones can search for missing persons. Smart homes can turn on the heater when we’re halfway home. And smart vehicle recorders can track where we’ve been. The ’smart’ is derived from the learning models generated by AI algorithms. Some of these models are trained on data that represents a large cross-section of a population to be used for general purposes. However, other models are personalised, which means the model is trained on personal data and then used to meet the requirements of one individual. For example, a wearable band with a general model might tell us when to drink water. But after collecting data about the particular person wearing the band, the model may be able to tailor a healthy diet to specifically suit the wearer’s lifestyle. Smart devices built on personalised models are more helpful and are considered to be the way of the future The final output of the project will be a personalised smart device that can collect the required personal data and automatically apply the appropriate privacy model before sharing the data in a diverse set of scenarios. This device could be used in a range of applications, such as driverless cars, smart homes, CCTV monitoring, and other AI-related devices to accelerate a boom in this high-tech sector. We are looking for the HDR candidate with the computer science or AI background. Quantum computing emulation platform - theQ Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. You will also be encouraged to apply for Sydney Quantum Academy top-up scholarships. This would include the stipend to be $35,000 per annum and increase the PhD duration to 4 years. You will also become a member of this academy. Contacts: Dr Simon Devitt Duration: 3 years (possible 6-month extension) School/Centre: School of Computer Science Centre: Centre for Quantum Software and Information Closing date: when filled Domestic applications only. TheQ is a low-cost quantum computing emulator, capable of perfectly mimicking a real quantum computing system, developed at UTS. Combined with custom apps for an iPhone, TheQ is targeted at high-school and undergraduate sectors to introduce the concepts surrounding quantum technology in a way that does not require graduate training in quantum information or theoretical physics. Designed as a system affordable to schools, universities and hobbyists, TheQ provides a platform to implement education programs to build a quantum literate workforce with the skills in a quantum enabled economy. Background in software engineering, online platforms, quantum information science, educational development and coding will be beneficial. Reducing injuries within the greyhound racing industry Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). An application for a top up scholarship is possible and fee waivers may also be considered for the successful candidate. Contact: Professor David Eager Duration: Doctoral Degree 3 years and Maters degree 2 years School: School of Computer Science and School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic and International applications accepted. UTS has been engaged to make recommendations that will lead to the reduction of injuries within the greyhound racing industry. We currently have a highly specialised team of HDR students and are looking to expand our ranks with the addition of a data scientist. The scope of the project includes but not limited to pattern recognition, advanced statistical analysis, feature engineering, experimental design and writing reports. UTS has a responsibility to each of its stakeholders in communicating its findings by way of reports thus strong English skills are a mandatory requirement. The position would suit a computer scientist, data engineer, data scientist or any similar degree with strong programming and statistical analysis skills. The perfect candidate have: programming skills statistical knowledge be able to meet strict deadlines work well in teams good time management skills very strong oral and written communication skills The right to be forgotten: GDPR modelling in cross-domain social networks Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt).Fee waivers may also be considered for the successful candidate. Contact: Associate Professor Tianqing Zhu Duration: 3 years (possible 6 month extension) School: Computer Science Centre: Centre for Cyber Security Closing date: when filled Domestic applications only. The project aims to develop a ‘right to be forgotten’ privacy preservation framework and erasure mechanisms that are effective even when information is derived from multiple related social networks. The right to be forgotten is a critical requirement of the European General Data Protection Regulation (GDPR), which is a data privacy preservation regulation that introduces a range of restrictions on companies that collect customers’ personal data. The regulation not only applies to businesses located within the EU but also to external organisations that offer goods or services to EU citizens. The project will output a framework that meets the requirements of the right to be forgotten; the framework will also be usable by Government to secure Australian cyberspace, and by industry, to protect their clients and increase profits. We are looking for HDR students with computer science background. Vibro-acoustic cloaking of biogenic structures in a host-inquiline relationship in termites Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Dr Sebastian Oberst Duration: 3 years (possible 6 month extension) School: School of Computer Science and School of Mechanical and Mechatronic Engineering Centre: Centre of Audio, Acoustics and Vibration Closing date: when filled Domestic and International applications accepted. Termites live in colonies of several million individuals, underground and in the dark. The substrate termites feed and live on is biogenically designed or modified to serve as a multifunctional, multi-scale material. Termites use this substrate to efficiently ventilate and air-condition their nest, to carry a maximum of load by using a minimal materials, as food storage, nursery or for defence of the colony and as communication channel. Yet, almost no details of how these different functions are achieved, are known. This project interfaces directly Biophysics with (Acoustic)Engineering to study a specific tri-trophic relationship of a certain ant species (predator), termites (prey, host) and inquilines (prey, parasite) and its nonlinear dynamics, but with focus on communication networks. The focus is here on studying the communication network characteristics and its species interactions (eavesdropping etc) by using the ‘active space’ concept of biology/biotremology and to relate this to the behavioural ecology of termites, their predators and competitors. Using the network and its input/output relations using theoretical considerations and experimental data, novel vibro-acoustic materials for camouflage are sought to be conceptualised, specifically for defence applications. The potential candidate should be self-driven and motivated, should have an Australian PR or citizenship, and a university degree in Engineering, Physics or Mathematics or comparable discipline. Any other project info (e.g. top ups, sponsor info): ARC Discovery Project, FEIT Vision-based smoke detection for bushfire surveillance Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Hongda Tian Duration: 3 years (possible 6-months extension) School: School of Computer Science Centre: Data Science Institute Closing date: when filled Domestic and International applications accepted. To prevent property damage and loss of human lives due to bushfires, smoke detection from image/video is deemed to be a promising approach to early detection and prediction of fire disasters. Despite advances, challenges still exist for developing robust vision-based smoke detection algorithms, which include reliably quantifying the visual characteristics of smoke and overcoming the limitations of devices in real applications. This research aims to establish computational models to address these challenges and develop novel machine learning algorithms for vision-based smoke detection. The candidate is expected to have a Master by research degree, or Honours degree with research component in relevant discipline (such as computer science, mathematics, data science, electrical engineering, or related field). The candidate also needs to have strong programming skills in Python/MatLab/C++. Electrical and Data Engineering 3D printed optical components Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted In a recent collaborative breakthrough, we have demonstrated the utilisation of thin film coatings to reduce not only Fresnel reflections from 3D printed optical components but also their scatter. The importance of this rests with the relaxation of post processing methods to remove surface roughness a main source of loss and degradation of component performance. This project will seek to advance the method, optimise material printing and develop high quality, robust optical components. Additive Manufacture of optical fibres Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted In 2020, Technologymagazine online described our invention of the 3D printed glass fibre as one of the top three most important breakthroughs in additive manufacture because of its potential to overcome the current limits of optical fibre fabrication technology in addressing future bandwidth and customised applications. This ongoing collaborative project seeks to continue that work as part of a larger effort to disrupt optical fibre fabrication. It will focus on improving optical losses for longer distance applications as well as demonstrating fibre types not possible otherwise. Additive manufacture of photonics Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted Using additive manufacturing in various photnonics applications, from components to waveguides and fibres. Advanced optical fibre fabrication and applications Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted With the establishment of a new state of the art modified chemical vapour deposition (MCVD) silica fibre fabrication facility at UNSW (with nine partner universities), project opportunities exist in a number of areas to explore new fibres and better understand the MCVD processing. Advanced optical fibre fabrication. Areas can include new Bi fibres (led by Prof. Peng at UNSW; Prof Canning is a Conjoint Professor) for amplifiers, lasers and sensors and novel structured fibres including photonic crystal fibres, Fresnel fibres, spun structured optical fibres and so on. Most recently, a new initiative at looking at special fibre design for high power fibre lasers has been funded by AORD - facilitated grants resulting in the first active spun structured fibres to be produced. 3D printing of Optical Fibres We first proposed and demonstrated the idea of using 3D printing to produce optical fibres, having done so using low cost 3D printers to manufacture preforms drawn into optical fibre on a tower. The key advantage is that by 3D printing arbitrary structure fibres are possible, moving away from the constraints of manual stacking that only allow non-ideal periodic structures – so-called photonic crystal fibres. We have shown in the past these are non-ideal solutions for optical waveguides and that the 1D nature of the fibre leads to more appropriate Fresnel conditions i.e. Fresnel fibres. This project will develop novel siica based 3D printing to demonstrate silica based preforms that can be drawn on a commercial draw tower system we have set up at UNSW. Working with various colleagues, simulation of these structures will help design a range of special fibres to print. 3D printing photonics Scope exist to explore a number of areas where Photonics can be advantaged by 3D printing. Further Reading: J. Canning, “Top up and top down: self-assembling and 3D printing custom photonic waveguides and components”, (KEYNOTE), International Conference on Emerging Advanced Nanomaterials, Newcastle Australia, (2018) and refs therein. K. Cook, G. Balle, J. Canning, L. Chartier, T. Athanze, M.A. Hossain, C. Han, J-E. Comatti, Y. Luo, G-D. Peng, “Step-index optical fibre drawn from 3D printed preforms”, Opt. Lett., 41 (19), 4554-4557, (2016). C. Han, J. Canning, K. Cook, M.A. Hossain, H. Ding, “Exciting Surface Waves on Metal-Coated Multimode Optical Waveguides using Skew Rays”, Opt. Lett., 41 (22), 5353-5356, (2016). Advanced satellite environmental modelling Scholarship: Successful applicants will receive a living stipend and full fee waiver during both their studies in Vietnam and Australia funded through the Joint Technology and Innovation Research Centre (http://jtirc.uet.vnu.edu.vn/), a research collaboration between the University of Technology Sydney and Vietnam National University Hanoi. Contact: Stuart Perry Duration: 3 years (possible 6 month extension) School: Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted. Overview: The Center for Multidisciplinary Integrated Technologies for Field Monitoring (FIMO) at the University of Engineering Technology, Vietnam National University Hanoi, together with the Perceptual Imaging Laboratory, School of Electrical and Data Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney is seeking applications from students wishing to undertake PhD studies on the topics listed below. Eligibility: Bachelors degree with honours or Masters degree in computer science, vision science or related field. Successful applicants will be expected to spend at least a year in Vietnam, studying at the University of Engineering Technology, Vietnam National University Hanoi, Vietnam, followed by a period of study at the University of Technology Sydney, Australia before returning to complete their studies in Vietnam. At the end of their studies, applicants will be awarded a PhD degree by both VNU Hanoi and UTS. To initially be accepted into the program, candidates must meet English proficiency requirement (IELTS 6.0) with demonstrated excellence in academic achievement (e.g. top venue publications). To progress to the UTS component of the program, candidates must have demonstrated research excellence during the initial stage and meet an English proficiency requirement of IELTS 6.5. The scholarship is open to all nationalities, but we encourage Vietnamese citizens in particular to apply. Successful applicants must be eligible to obtain a student visa to study in both Vietnam and Australia and be prepared to spend at least one year studying in Vietnam. Funding: Successful applicants will receive a living stipend and full fee waiver during both their studies in Vietnam and Australia funded through the Joint Technology and Innovation Research Centre (http://jtirc.uet.vnu.edu.vn/), a research collaboration between the University of Technology Sydney and Vietnam National University Hanoi. Contact Details: Please contact A/Prof Stuart Perry (Stuart.Perry@uts.edu.au) and A/Prof Thi Nhat Thanh Nguyen (thanhntn@fimo.edu.vn) to enquire about these topics. Project Description: Advanced Satellite Environmental Modelling Satellite imagery has a wide variety of uses and the potential to help improve the productivity of agriculture and the effectiveness of urban management. This project is concerned with the use of advanced machine-learning based computer vision techniques to classify and analyse images of the environment in Vietnam and other countries. This may involve computer vision for the analysis of water usage, rice production, forest clearing activities, urban development or other applications. Aerosol microfluidics Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Professor David McGloin Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted. The development of microfluidic devices over the past couple of decades has led to a significant new range of analytical tools, both in chemistry and biology. Such tools are based on the confinement of liquid within microscopic channels, and can now be incredibly sophisticated 3D devices, with valves, heating elements, and a myriad of other components incorporated into their design. The goal of this project is to develop a similar platform to microfluidics, but with the aim of confining and monitoring airborne particles. These ‘aerofluidic’ chips will incorporate optical, electrical and magnetic confinement techniques, and look to harness cutting-edge laser writing to create optical waveguides and channels in glass substrates. The aim is a paradigm shift in the analysis of airborne particles, opening up disposable, low-cost devices that will allow a range of monitoring tasks to be carried out. The work will involve the development of the aerofluidic devices, making use of standard microfabrication techniques, integration of optical trapping and spectroscopy, as well as examining new methods for monitoring particles in such a device through the creation of built-in optical cavities. The challenges to be overcome include how to keep high-velocity liquid particles away from the walls of the device. The project is suitable for someone with a background in physics, photonics, analytical chemistry and electrical/electronic/mechanical engineering and related backgrounds. Artificial Intelligence for management of electric vehicles and vehicle to grid (V2G) resources optimization Scholarship: This project includes funding for a living stipend scholarship of $38,092 per annum (tax-exempt). RACE for 2030 will also supply up to $3,000 per annum for expenses for the candidate, for items such as a computer, publishing fees, travel or conference costs. Fee waivers may also be considered for the successful candidate. Contact: Professor Jahangir Hossain Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: 17 November 2021, 5 PM (AEDT) Domestic and International applications accepted. We encourage female identifying and Indigenous applicants to apply. Short description This project aims to develop and implement intelligent techniques to manage the charging and discharging of electric vehicle (EV) batteries and design EV management framework using state of the art artificial intelligence algorithms for addressing major challenges that arise in the deployment and management of EVs in residential and commercial levels. The key focus of this project is to develop new tools to optimize the infrastructure and maximize the benefits for businesses and consumers with distributed energy resources including EVs and photovoltaic systems. The outcomes of this project will be to produce new applied research utilizing AI in EV management and V2G resource optimization and, thus contribute in creating new jobs and reduce greenhouse gas emissions. Project description The PhD project will be completed in the School of Electrical and Data Engineering and is funded by a generous 3-year scholarship by the RACE for 2030 Collaborative Research Centre in collaboration with industry partner Planet Ark Power. The following areas will be the key focus of this project: Automated coordination of EVs’ and Photovoltaic (PV) systems’ operations: Application of AI and machine learning to identify optimal operations of charging and discharging based on the availability of PV output power, energy price, state of charging and forecasted EVs’ demand for residential and commercial sectors to maximize benefits for consumers and businesses; Vehicle to grid (V2G) resource optimization: Use of AI techniques and machine learning algorithm to optimize V2G resources dispatching for owners’ profit maximization and preference preservation while preventing grid congestions, complementing intermittency of the renewable-based power generations, smoothing of the power demand profiles, reducing peak demand, and minimizing electricity price-spikes due to supply-demand mismatch; Predictive optimization of charging stations’ sizing and placement: Use of forecast charging demand of EV and EV penetration levels to optimize sizing and placement of charging stations in commercial microgrids. This PhD will explore different AI-based techniques which will be implemented not only to predict optimal solutions but also to estimate uncertainty in EV usages and charging while combining with methods in Human Interpretable Machine Learning to ensure EV owners and businesses can have confidence in the models. The outcomes of this project will be to produce new applied research utilizing AI in EV management and V2G resource optimization. The results will be verified using a real time simulator (OPAL RT) and power systems equipment available at Tech-Lab UTS. The unique and competitive ideas developed and verified using real-time simulator will be published in reputed journals and conferences This PhD will be completed through a PhD by publication/compilation or thesis with a minimum of three peer reviewed publications and will commence with an industry focused Rapid Review. This PhD will also be supported by an Industry Reference Group throughout the project providing the opportunity to develop advanced research skills, contribute to an important global issue and engage meaningfully with industry. Eligibility Applicants should have a first-class honours or masters degree or equivalent in a related discipline, OR a combination of an upper second-class honour’s degree or equivalent in a related discipline together with a minimum of five years equivalent full-time professional work experience in a relevant field. Applicants must be eligible for enrolment in their chosen course at UTS. It is recommended that students obtain relevant postgraduate information from the relevant university before pursuing a scholarship inquiry. Applicants must be studying full time. Skills and experience In addition to the eligibility criteria, candidates should also have the follow skills and/or experience: Power systems and renewable energy engineering, electric vehicle (EV) operation and integration of EVs into the grid Mathematical modelling of distributed energy resources including EVs and photovoltaic systems Artificial intelligence and mathematical optimization, preferably with applications to power system Programming in MATLAB and Python Fluent written and verbal communication skills During the competitive selection process, candidates will also be assessed upon their ability to: Independently pursue their work Collaborate with others, including industry and research partners Analyse and work with complex issues and Formulate scientific and industry focused texts To apply, you need to send your CV and a cover letter outlining your relevant skills and experience. Cement based sensors Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted Assessment of photonic of sensors for long term performance in cement and concrete for buildings. Creating a Perceptive Mobile Network Using Joint Communication and Sensing Scholarship: This project includes funding for a living stipend scholarship at the rate of $28,092 per annum (tax-exempt). Fee waivers may be considered for the successful candidate. Contact: Dr Andrew Zhang Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Centre: Global Big Data Technologies Centre Closing date: when filled Domestic and International applications accepted. This project aims to develop foundational technologies for an innovative perceptive mobile (cellular) communication network that is also capable of ubiquitous radio sensing. It is expected to generate groundbreaking theorems and algorithms that will significantly advance the knowledge of joint communication and sensing. The intended outcomes are an innovative large-scale sensing solution capable of real-time 3D-plus radio imaging of the world, and enhanced communications with improved quality and reliability. The technology will revolutionize traditional communication-only mobile networks. It will enable and boost expansive radio sensing applications in e.g. transportation, energy, agriculture, and security. Students are expected to have a strong background on signal processing, information theory, and/or network techniques, and have a good knowledge on mobile communication networks and/or radar systems. Skills on Matlab programming are desired. DEFENCE SENSITIVE: Laser Weapons in the sky through optical fibres Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic applications only This project will explore the use of drones carrying optical fibres that deliver laser light for sensing and defence applications. By keeping the heavy laser system on the ground high powers can be accessed this way that might otherwise not be possible. This may be one of the very few tailored technology solutions that advantages a small population but large land mass like Australia's - a centralized laser system feeding laser light into dozens of fibre tethers to UAVs and other vehicles can be used to create laser shields against incoming missiles for example. Can only be a domestic security cleared student motivated to protect Australia. Please do not advertise this project specific details publicly for obvious reasons. DEFENCE SENSITIVE: Optical Fibre Tethers for Suspended Air Sensing between Micro satellites and/or drones Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic applications only This project will assess the feasiblity and test tethering micro satellites and drones to provide high bandwidth, low latency and secure communications and other applications. Suspended aerial fibre sensors will be explored. Developing optical manipulation and imaging tools for extreme engineering environments Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). An application for a top up scholarship is possible and fee waivers may also be considered for the successful candidate. Contact: Professor David McGloin Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted. Current optical manipulation techniques work in highly controlled environments on well-defined particles. For applications in environments where these conditions are not readily met, there is still the need for examining particle properties and dynamics. One example would be to trap and analyse particles in an engine, where contaminants, pressure and lack of optical access work against single particle, optically based, analysis tools. In this project, the goal will be to develop fibre based optical manipulation and imaging tools that can work in extreme environments such as engines and field-based monitoring systems. It will also explore how such tools could be used to study cloud seeding. The work will involve solving problems around carrying out imaging through thin optical fibres, extracting useful data about particle properties from the same fibre, and how to build robust optical systems in places where optics don’t normally need to go. On the application side, the work will explore trapped particle behaviour in these environments and look at particle changes over time. The project is suitable for someone with a background in physics, photonics, analytical or physical chemistry and environmental/electrical/electronic/mechanical engineering and related backgrounds. The project will involve the development of the optical manipulation and imaging instrumentation and their integration into the engineering environments under study. The project will be collaborative between Prof. McGloin’s group and other Engineering groups, in particular, that of Dr Nic Surawski. Development of an optical low-loss metamaterial in the IR Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Professor Francesca Iacopi Duration: 3 years (possible 6 month extension) School: Electrical and Data Engineering Closing date: when filled Domestic candidates only. The miniaturisation of optical systems (for advanced cameras, LiDAR systems, fast communications, etc) is lagging far behind that of electronics. However, it is a crucial problem to be solved in order to enable the next technological revolution. Do you want to help discover new technological solutions? Plasmonics, polaritonics and their combination enable the manipulation of light at the nanoscale, at size scales much smaller than the diffraction limit, which is a “holy grail” for applications from integrated optical technologies for high resolution imaging to chemical-selective sensing for medicine and biology. You will be part of the Australian Research Council Centre of Excellence in Transformative Meta-Optical Systems (tmos.org.au), within a world -leading domestic and international research team, enabling the manipulation of light in a microchip through advanced metamaterials. This work will be based at the Faculty of Engineering and IT, in the UTS central Broadway campus in Sydney. Electrical and Electronic Engineering at UTS is ranked #140 worldwide, with state-of-the-art measurement and fabrication laboratories. Pre-requisites: MSc by Research in Physics, Nanotechnology, Materials Science or analogous field Candidates with proven knowledge and skills in at least a few of the areas below are preferred: Optics and nanophotonics Thin –film fabrication Finite Elements Modelling and /or Finite Difference Modelling Good- quality publications Excellent communication skills Works well in a team Female applicants as well as individuals from underrepresented groups are strongly encouraged to apply. For further inquiries please contact Professor Francesca Iacopi, francesca.iacopi@uts.edu.au Development of novel, low carbon footprint cementitious materials for construction, architecture, smart cities and embedded optical sensing. Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. $20,000/yr for an APA award or other meritorious scholarship holder Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic applications accepted only In a recent collaborative breakthrough, we have demonstrated the utilisation of thin film coatings to reduce not only Fresnel reflections from 3D printed optical components but also their scatter. The importance of this rests with the relaxation of post processing methods to remove surface roughness a main source of loss and degradation of component performance. This project will seek to advance the method, optimise material printing and develop high quality, robust optical components. Effective learning for digital-twin computing Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). An application for a top up scholarship is possible and fee waivers may also be considered for the successful candidate. Contact: Dr Guoqiang Zhang Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Centre: Centre for Audio, Acoustics and Vibration Closing date: when filled Domestic and International applications accepted. Digital-twin computing refers to the framework of creating and learning digital (or machine learning) models to mimic the behaviours of real-world entities. The resulting models can be deployed to improve the wellbeing or effectiveness of the entities via prediction and/or control. One key step behind the framework is the design of learning strategies for the models. In this PhD project, the candidate will conduct research on the learning procedure of the models. The real-world entities to be considered in the PhD project may include, for example, one or more persons performing a particular task (e.g., driving a car, playing football, or playing a video game), or public services like traffic light control. Commonly the same model applies to many real-world entities. A natural research direction is to employ a parallel and distributed learning framework. The outcome will be novel strategies that enable effective learning for digital-twin computing. Enabling the collocation of 3G/4G/5G base station antenna arrays Scholarship: A living stipend scholarship of $28,000 per annum (tax-exempt) and tuition fee waiver are available. Contact: Dr Can Ding Duration: 3 years (possible 6 month extension) School: Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted. Base station antenna technologies will play a crucial role in determining the performance and the deployment costs of 5G systems. To ensure 5G coverage, many 5G base stations will need to be installed. Acquiring new sites for base station antennas would lead to substantial increases in costs and environmental pressure. Therefore, the most promising approach envisioned by the mobile industry to address these economic and environmental challenges is to integrate 5G base station antennas into the existing 3G/4G ones, thus reducing the number of new base station antenna sites required. However, it faces one scientific challenge – the severe electromagnetic interference between antennas caused by their close proximity. This electromagnetic interference causes high correlations among the signals received by the different antennas and introduces unacceptable distortions of the antenna radiation patterns and degradation of the impedance matching performance. The net result is a complete deterioration of the performance of the overall communication network including a reduction of the data rate, channel capacity and coverage. The aims of the proposed project are to develop and validate new scientific methods and engineering techniques that will empower the collocation of 3G/4G/5G antennas, thus enabling cost-effective 5G infrastructure deployment in Australia and internationally. The research efforts will focus on the reduction of electromagnetic interference associated with integrated 3G/4G/5G base station antenna arrays. Enabling Mission Critical Communications over Wireless Networks Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Mehran Abolhasan Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Centre: Centre for Autonomous Systems Closing date: when filled Domestic and International applications accepted Wireless networks have transformed the way we communicate, socialise and conduct our daily work. Wireless Network enabled the birth of a diverse range of applications over the past 10 years. Such applications range from gaming, social networking all the way to various types of business applications. However, many of such applications have been designed with one key limitation in mind. That is, Wireless network tend to be unreliable. It is not uncommon to see network dropouts or link failures as you travel and use various networking application. This limitation is generally tolerated and enables above application to continue to operate without significant impact on their operation once a link is restored. However, with the emergence of 5G Wireless networks, which promises to provide high level of capacity and reliability, the question is being asked now: Can wireless network be made reliable and agile enough to run Mission Critical applications? Mission Critical applications must operate over networks which have high levels of reliability otherwise it could result in catastrophic outcomes such as loss of life. There are a diverse range of applications, which would benefit from a Wireless network which can achieve a high level of reliability and low-latency. These applications range from Vehicular Network communications and Coordination, Telehealth/Remote Surgery, management of Industrial IoT sensor and actuations and more. This project will conduct detailed investigation in the various layers of the current Wireless communications stack and propose new models, algorithms and protocols which aim to enhance the reliability of wireless networks and reduce communications latency. Experience Needed: Strong mathematical background, Knowledge of Optimisation techniques, AI/ML, Strong knowledge of Wireless networking, Solid scripting and programming in languages such as C ++ and Python. Extending the lifetime of switching power converters Scholarship: This project includes funding for a living stipend of $33,000 per annum (tax-exempt). Fee waivers may be considered for the successful candidate. Contact: Professor Dylan Lu Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted This project aims to address the need for a longer lifespan of power conversion systems that can withstand the failure of its key components. This is achieved by developing more reliable power converter circuits whilst reducing the stress of the components. This project will generate new circuit design and control techniques for power and energy systems, especially in dealing with reliability issues. The expected outcome of this project includes a reduction of the failure rate of power converters by at least 50%. This should provide benefits for many sectors including emerging technologies in particular renewable energy, electric vehicles and energy storage systems seeking reliable power supply and for the environment with reduced e-waste production. This project is funded by the Australian Research Council Discovery Projects. Fibre and fibre gratings sensors Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted Fibres and fibre Bragg and long period gratings continue to be explored extensively for sensing and communications. From individual point sensors to distributed point sensing and continue time of flight fibre sensing are being assessed across a number of industries and sectors. The need to reduce latency means their hardware based encoding of sensor identity with in spectral or time domains is attractive and can make up for initial up-front costs when scalability issues are considered. Further they can be immune interference making them suitable for a range of environments. Various projects across this field exist. Examples include: Distributed Acoustic Sensing In collaborative work with colleagues in Brazil we are exploring the use of acoustic and vibration detection using coherent pulses of light. This project will involve setting up a system in Sydney and exploring novel variations to this technology. Fibre Gratings A range of projects can exist around this technology from grating design to new applications, both passive and active. Fibre DFB lasers were pioneered in this group, including helical DFBs where helical generation leads to stable and stronger outputs. The process of regeneration permits the strongest high temperature gratings feasible allowing fibre lasers to be only limited by the gain medium. Students are welcome to suggest projects and interests as well as discuss new areas. Details are limited for potential IP considerations. Further reading: J. Canning, K. Cook, “Monitoring Australian Utility Poles”, Asia Pacific Optical Sensors (APOS2018), Matsue, Japan (2018). J. R. Galvão, A. B. Di Renzo, P. E. Schaphauser, A. Kalinowski, J. Canning, C. R. Zamarreño, J. C. C. da Silva and C. Martelli, “Fiber Bragg Grating Interrogation Techniques Applied to Horse Gait Analysis”, IEEE Sensors J. 18 (14), 5778-5785, (2018). F. Mezzadri, F. C. Janzen, G. Martelli, J. Canning, K. Cook and C. Martelli, "Optical-fiber sensor network deployed for temperature measurement of large diesel engine," IEEE Sensors J., 18 (9), 3654-3660 (2018). J. Canning, “Regeneration, regenerated gratings and composite glass properties: the implications for high temperature micro and nano milling and optical sensing” Invited, Measurement, 79, 236-249, (2016). A.A. Pohl, O.A. Roberson, R.E. da Silva, C.A.F. Marques, P. de T. Neves Jr., K. Cook, J. Canning, R.N. Nogueira, “Advances and New Applications Using the Acousto-Optic Effect in Optical Fibers”, Invited, Photonic Sensors, 3 (1), 1–25, (2013). J. Canning, “Fibre Gratings & Devices for Sensors & Lasers”, Invited, Lasers & Photon. Rev., 2(4), 275-289, Wiley, USA (2008). J. Canning, “Fibre lasers & related technologies”, Invited, Opt. & Las. In Eng., 44, 647-676, (2006). Foundations of IoT timing Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). An application for a top-up scholarship is possible and fee waivers may also be considered for the successful candidate. Contact: Professor Darryl Veitch Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Centre: Global Big Data Technologies Centre Closing date: when filled Domestic and International applications accepted. Every computer on earth has a software clock on board which is essential for its own operation as well as that of applications running on it. The vast majority of these clocks are kept synchronised using a system called NTP that connects to clocks of greater accuracy over the Internet. The problem is this system has many problems, leading to incorrect timestamps, which in turn leads to software failures and likely system collapse under the weight of the Internet of Things (IoT), which will grow to trillions of devices - soon. Timekeeping is the silent Achilles Heel of many systems, for example so much of the Big Data sets now routinely collected consist of timestamps, but can we trust them? The Timing Laboratory at UTS is working to solve the research problems critical to the design of a global, networked timing system which is highly accurate, robust and reliable, and whose performance can be trusted and verified, even at the scale of the Internet of Things. It operates a state of the art timing testbed which includes an atomic clock, multiple high-end GPS receivers, and specialised timing appliances donated from leading manufacturers. In the past this project has received funding from the ARC, Google, industry-leading timing hardware manufacturer Symmetricom, and the FreeBSD Foundation, and it has a close relationship with the National Measurement Laboratory (NMI), Australia’s guardian of reference time, and its contributor to the global UTC timing standard. Foundations of IoT timing The hardware resources and timing needs of IoT devices are diverse. They include the particular challenges of wireless and low power devices, which breaks the normal assumption in wired networks of uninterrupted access to a time server over the Internet. It includes the extra dimension of the Internet of Moving Things (such as drones), and of Industrial IoT, where devices, despite (often) being wirelessly connected, have very strict timing requirements, with catastrophic consequences should these fail. The challenge is to ensure the timing needs across this diverse set are met, securely and reliably, at a scale of billions to trillions of devices. You will build on the Timing Laboratory's strengths in core timing infrastructure design, and robust synchronisation algorithms, to design a hardened timing architecture for IoT devices of all kinds. You will work with the NMI and International partners to trial the solution at scale, and contribute to standards in the area, and you will investigate new approaches, including blockchain, to ensure trusted timestamping. Candidates will have a strong background in computer networking, programming (Matlab, Python, C), and statistical analysis, with a good knowledge of wireless networking and/or embedded device communications. Hardening network timing infrastructure Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). An application for a top up scholarship is possible and fee waivers may also be considered for the successful candidate. Contact: Professor Darryl Veitch Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Centre: Global Big Data Technologies Centre Closing date: when filled Domestic and International applications accepted. Every computer on earth has a software clock on board which is essential for its own operation as well as that of applications running on it. The vast majority of these clocks are kept synchronised using a system called NTP that connects to clocks of greater accuracy over the Internet. The problem is this system has many problems, leading to incorrect timestamps, which in turn leads to software failures and likely system collapse under the weight of the Internet of Things (IoT), which will grow to trillions of devices - soon. Timekeeping is the silent Achilles Heel of many systems, for example so much of the Big Data sets now routinely collected consist of timestamps, but can we trust them? The Timing Laboratory at UTS is working to solve the research problems critical to the design of a global, networked timing system which is highly accurate, robust and reliable, and whose performance can be trusted and verified, even at the scale of the Internet of Things. It operates a state of the art timing testbed which includes an atomic clock, multiple high-end GPS receivers, and specialised timing appliances donated from leading manufacturers. In the past this project has received funding from the ARC, Google, industry-leading timing hardware manufacturer Symmetricom, and the FreeBSD Foundation, and it has a close relationship with the National Measurement Laboratory (NMI), Australia’s guardian of reference time, and its contributor to the global UTC timing standard. Hardening Network Timing Infrastructure The existing timekeeping system for the Internet, depended on for billions of end computers, is vulnerable. Building on the Timing Laboratory’s proven RADclock approach to robust synchronisation over noisy networks, you will rewrite the core architecture of the global timekeeping system to protect the underlying atomic hardware, harden against innocent or malicious overloads, circumvent the critical problem of timing asymmetry, and provide a self-monitoring capability to monitor and ensure accuracy. Your work will help insulate the global network from timing attacks and other timing anomalies which carry a high economic cost. You will work with the NMI to perform Australia-wide public trials of the technology, help contribute to Internet standards in the area, and contribute to Open Source software, including in the Linux kernel. Candidates will have a strong background in computer networking, programming (Matlab, Python, C), and optimisation. High-speed, Low-Power and Secure Technologies for Internet of Things Applications Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Mehran Abolhasan Duration: 3 years (possible 6-months) School: School of Electrical and Data Engineering Centre: Centre for Autonomous Systems Closing date: when filled Domestic and International candidates accepted. Internet of Things (IoT) is one of the key technologies with the potential to create a multi-trillion-dollar Industry. IoT is already making significant impact on many existing Industries in a number of ways. This includes enabling business process improvements and better management of operations at scale, while opening ever-growing niche business opportunities. The existing impact of IoT can be seen in many numbers of Industries such as Agriculture, Mining and Transportation, where IoT has played a major role in enabling automation and monitoring. However, with the proposition of new technologies such as 5G, which provide a platform to develop and provision new types of services, the range of applications for IoT is set to grow. This includes a new generation of tactile applications and services with mission critical operations, such as remote surgery, driverless cars and more. Each new application may introduce new research challenges before an IoT solution can be successfully developed. Across a range of challenges mentioned above some of the key research challenges that IoT faces includes: 1. Security and 2. Application specific Connectivity. In terms of Security, much research still needs to be conducted to ensure IoT Devices and the data they generate are secure. This problem needs to be addressed at different stages and layers of the IoT stack. In terms of Application specific connectivity, since IoT devices have different transmission and QoS requirements, this issue will have to be addressed based on the application requirement. For example, one application may require low data-rate but long-range connectivity, and another may require ultra-reliable connectivity with low-delay and high-speed connectivity. Furthermore, another application may require each IoT device to be located in places where recharging of batteries may not be feasible, hence the IoT devices must operate and transmit data in an energy efficient manner. This project will explore a number of research topics based on the above challenges. Where will the research be conducted: The above research will be conducted in the RFCT lab at UTS, which is a new lab with state of art facility, enabling design, modelling and prototyping of next generation IoT devices. Training and research opportunities: You will develop your skills in designing IoT, working with potential industry partners, developing new innovative IoT technologies solving real-world problems. What we are looking for: You will ideally have a First-class Honours or a Masters by research. You will have skills in programming (required), good knowledge of communications technologies and protocols (required), Electronics prototyping (desired), Machine learning and analytics (desired) Software Defined Network Architecture and protocol design for Next generation Wireless networks High-speed millimetre wave wireless communications Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). An application for a top up scholarship is possible and fee waivers may also be considered for the successful candidate. Contact: Professor Xiaojing Huang Duration: 3 years (possible 6-months) School: School of Electrical and Data Engineering Centre: Global Big Data Technologies Centre Closing date: when filled Domestic and International candidates accepted. Increasing demand for high speed wireless communications systems means that new signal processing algorithms and hardware implementations are necessary to meet low cost and high performance requirements. This research project will investigate effective digital signal processing algorithms and efficient hardware design to realise high speed wireless communications in real-time. PhD candidates should have both theoretical background and hardware implementation experience. The main duties/responsibilities: Perform literature review to understand the state-of-the- art in high capacity wireless communications technologies such as the emerging 5G systems and millimeter wave systems Conduct scientific research to advance the wireless communications and remote sensing technologies, increase the system capacity, and improve the system performance Participate in research projects, including undertaking algorithm simulations, reporting simulation results, and providing solutions to research problems Write research papers on new theories, algorithms, and implementation solutions, and publish the results in high quality journals and premier international conferences Prospective students graduated or going to graduate from Electrical and Electronic, Communication and Networking, Signal Processing, Physics or Applied Science, or related disciplines with first class honors degree, or equivalent are invited to apply. This is a great opportunity for a candidate that has strong research experience and publication track record in wireless system design, modulation, coding, multiple input multiple output beamforming algorithm development, interference cancellation, detection and analysis. Funding Notes We are offering a PhD scholarship in the field of wireless communications and signal processing at University of Technology Sydney (UTS), based in Sydney, Australia. For the successful applicant, the scholarship fully covers the university fees and research expenses, and provides additional allowance to cover living costs for up to 3.5 years: References: Please find out more about my research areas on https://www.uts.edu.au/staff/xiaojing.huang . Lab-in-a-fibre and Lab-on-a-waveguide sensing technologies Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted Chemical and biochemical sensing, particularly around surface waves and plasmon generation, especially in the energy and environmental sectors (and also health) is one of the fastest growing research fields in photonics. The silica fibre host is perhaps the most desirable platform for a number of reasons including the ability to perform safe and remote interrogation and to have mufti-functionality. Various project opportunities to develop novel sensors in fibre and integrated form, some using the technologies briefly described above, are available. In particular, laser processing of surfaces is an extremely important project to both understand and control robust attachment of molecules to surfaces. Proposed in 2005 by Canning when presenting an invited talk in China, lab-in-a-fibre technology platform has taken many forms (lab-in-fibre, lab-on-fibre, lab-on-a-fibre, lab-around-fibre and so on) - more than decade later in 2017 there was a dedicated symposium workshop at a major photonics event emphasising the growth of the topic. Further reading: G. Dutra, J. Canning, W. Padden, C. Martelli, and S. Dligatch, "Large area optical mapping of surface contact angle," Opt. Express 25, 21127-21144 (2017) M. A. Hossain, J. Canning, Z. Yu , S. Ast, P. J. Rutledge, J. K.-H. Wong, A. Jamalipour, M. J. Crossley, “Time-resolved & temp. tuneable measurements of fluorescent intensity using a smartphone fluorimeter”, Analyst, 142, 1953-1961, (2017). Md. A. Hossain, J. Canning, S. Ast, K. Cook, P. Rutledge, A. Jamalipour, “Combined “dual” absorption and fluorescence smartphone spectrometers”, Opt. Lett., 40 (8), 1737-1740, (2015). M. A. Hossain, J. Canning, K. Cook, A. Jamalipour, “Smartphone Laser Beam Spatial Profiler”, Opt. Lett., 40 (22), 5156, (2015). Md. A. Hossain, J. Canning, S. Ast, P. Rutledge, T.L. Yen, A. Jamalipour, “Lab-in-a-phone: Smartphone-based Portable Fluorometer for Off-site pH Measurement of Environmental Water”, IEEE Sensors, 15 (9), 5095-5102, (2014). J. Canning, A. Lau, M. Naqshbandi, I. Petermann, M.J. Crossley, “Measurement of fluorescence in a rhodamine-123 doped self-assembled "giant" mesostructured silica sphere using a Smartphone as optical hardware”, Sensors, 11 (7), 7055-7062 (2011). MAC Protocol Design for Underwater Communications Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt) and a Topup of $5,500 per annum (tax-emempt). Fee waivers may also be considered for the successful candidate. Contacts: Dr Ying He Duration: 3 years (possible 6 month extension) School: School of Electrical and Data Engineering Closing Date: 15 August, 2021 Domestic applications only. The Opportunity A fully funded PhD Scholarship is available for an outstanding candidate to work on MAC Protocol Design for Underwater Communications at UTS, in collaboration with Australia’s Defence Science and Technology Group. As part of the PhD program, the student will be expected to present their findings at international conferences and forums and publish their work in international journals. The PhD student will also benefit from practical, hands-on research experience in a Defence setting. Candidate Requirements This project will suit students with a strong background in telecommunications, wireless communications or computer science. Candidates are required to: • Have a Bachelor’s degree with a significant individual research component (preferably Honours) or a Master’s degree in any of the fields described above or a related field. • Be an Australian citizen, and currently residing in Australia. • Meet the eligibility criteria for PhD candidature at UTS. • Experience in MAC layer design and optimisation will be an advantage. • Programming experience in the following languages/platforms is preferred: NS2/3, C/C++, Python and Matlab. How to apply Potential candidates should contact Dr Ying He (Ying.He@uts.edu.au) to express interest, by 15th August 2021. Please provide a one-page cover letter addressing any information relevant to your interest in the project, CV, academic transcripts and two references. Nerve and muscle activation by rotating permanent magnets Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contacts: Associate Professor Peter Watterson Duration: 3 years (possible 6 month extension) for PhD candidates or 2 years for Masters candidates School: School of Electrical and Data Engineering Closing Date: when filled Domestic and International applications accepted. Nerve activation is emerging as a means to treat many debilitating medical conditions such as pain, muscle atrophy, depression and muscle spasticity. A full-time Master of Engineering (Research) or PhD place is available to advance a new class of painless, noninvasive magnetic nerve activators, based on high-speed rotation of permanent magnets. A proof-of-concept prototype device using two magnets has already been designed, built and tested, with the early positive results published believed to be a world first (J. Physiology doi:10.1113/JP271743; Neuromodulation doi: 10.1111/ner.12958, Paper INS19-0407). The research undertaken will include: computer modelling to determine the electric field generated within human limbs and the resulting transmembrane potential created in nerves within the limb; the design of new magnet configurations and devices to optimise the membrane potential; testing of prototype devices on animal and human nerves in collaboration with neuroscience researchers (subject to ethical approval being sought and granted). Applicants must have a strong mathematical background and aptitude, preferably with knowledge of electromagnetics (Maxwell equations for electromagnetic vector fields). Next generation smart materials for smart sensors Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted Embedding mechanical, optical, chemical and other sensors and other properties into new mateirals for buildings and infrastructure to make them smarter. Optimal design of biogas power generation system in wastewater plants Scholarship: This project includes funding for a living stipend of $38,000 per annum (tax-exempt). Contact: Associate Professor. Li Li Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: 15/11/2021 Domestic applications accepted only Project description A highly competitive scholarship is available to support a candidate to undertake a 3-year Industry PhD research project at University of Technology Sydney. The PhD project will be completed in the School of Electrical and Data Engineering and is funded by a generous 3-year scholarship by the RACE for 2030 Collaborative Research Centre in collaboration with industry partner Sydney Water. This PhD project will carry out research on the optimal planning and operational strategy for biogas power generation system design in wastewater treatment plants (WWTPs). The main objective of this research is to cover the research outputs listed below: Conduct techno-economic feasibility for biogas usage in WWTP. Provide a model by which the potential of WWTP facilities for optimal planning, and operation can be calculated. Design control strategies to maximize its revenues when participating in energy markets. Provide a guide and framework that will add value to the wastewater treatment process. This PhD will be completed through a PhD by publication/compilation or thesis with a minimum of three peer reviewed publications and will commence with an industry focused Rapid Review. This PhD will also be supported by an Industry Reference Group throughout the project providing the opportunity to develop advanced research skills, contribute to an important global issue and engage meaningfully with industry. Eligibility Applicants should have a First-Class Honours or Master’s Degree or equivalent in a related discipline, OR a combination of an upper second-class honour’s degree or equivalent in a related discipline together with a minimum of five years equivalent full-time professional work experience in a relevant field. Applicants must be eligible for enrolment in their chosen course at University of Technology Sydney. It is recommended that students obtain relevant postgraduate information from the relevant university before pursuing a scholarship inquiry. Applicants must be studying full time. Skills and experience In addition to the eligibility criteria, candidates should also have the follow skills and/or experience: Excellent written and verbal communications skills. Competence in mathematical foundations and computational/statistical thinking Ability to produce high-level literature reviews Familiar with the integration of renewable energy resources and energy storage systems (preferred) Research experience with PV generation, biogas technology, electricity market, planning, and operation (preferred) Working experience in the energy sector (preferred) Knowledge about the process or chemical engineering (preferred) During the competitive selection process, candidates will also be assessed upon their ability to: Independently pursue their work Collaborate with others, including industry and research partners Analyse and work with complex issues and Formulate scientific and industry focused texts Radio sensing and pattern analysis Scholarship: This project includes funding for a living stipend of $22,000 per annum (tax-exempt). Fee waivers and top-ups may also be considered for the successful candidate. Contact: Dr Andrew Zhang Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Centre: Global Big Data Technologies Center Closing date: when filled Domestic and International applications accepted The UTS Radio Sensing and Pattern Analysis (RASPA) laboratory devotes to developing ubiquitous radio sensing and analytics technologies, by combining wireless signal processing and machine learning techniques. We focus on two major research areas in this lab. (1) Building ubiquitous radio sensing infrastructure using joint communication and radar sensing techniques. In one project, we are studying how to evolve modern communication only mobile network (such as 5G) to one with simultaneous radar sensing capability, by sharing the transmitted signals and most of system modules. (2) Harvesting information from radio signals by combining wireless signal processing, pattern analysis and machine learning techniques. The aim is to extract information from the received radio signals for detecting, tracking, and identifying objects, activities and events in the surrounding environment. In one project, we are developing an integrated solution for Health, Safety and Security using WiFi Sensing, and in another project, we are developing an integrated miniature Video and Radio Sensors for 3D sensing and object tracking. Reconfigurable conformal transmitarrays for 5G applications Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Peiyuan Qin Duration: 3 years (possible 6 month extension) School: Electrical and Data Engineering Centre: Global Big Data Technologies Center Closing date: when filled Domestic and International applications accepted. Conformal transmitarray antennas are critical technologies for wireless communication systems for Airborne Platforms. For these platforms, conformal antennas, which are designed to follow the shapes of various mounting platforms, are highly desired in order to meet the aerodynamic requirements. This project will focus on smart conformal transmitarrays with independent beam steering capabilities for 5G applications. The main duties/responsibilities: 1. Conduct scientific research to advance the technology of reconfigurable conformal transmitarrays, including undertaking algorithm simulations, reporting simulation results, and providing solutions to research problems. 2. Write research papers on new theories, algorithms, and implementation solutions, and publish the results in high quality journals and premier international conferences. Prospective students include undergraduate students in the final year, postgraduate students in the final year, and current PhD students in the first year (for dual-degree). The students will have access to the well-equipped laboratories including a compact range anechoic chamber up to 90 GHz, and mm-wave and THz testing facilities. The students will also have opportunities to attend international conferences during their study. Minimum requirements are as follows: 1. Students with strong publications and/or in top 5% of students in their schools. 2. English: IELTS >6.5 (writing band >6); TOFEL 60-78, writing > 21 (Internet based). 3. Bachelor degree in electronic engineering, having a good knowledge of Electromagnetic Fields and Microwave Technologies. 4. Highly self-motivated and strong interests in research. References: Please find out more about my research areas on https://www.uts.edu.au/staff/peiyuan.qin Self-assembled photonics Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted Self-assembling high-quality silica wires from nanoparticles with highly uniform porosity was pioneered in our group. It has opened a new approach to fabricating waveguides and devices in photonics. A range of potential project areas exists in this topic spanning fundamental to applied. For example: Optical wire chemical and biological sensors Recent innovative breakthroughs enabling the self-assembly of photonic waveguides using nanoparticles will be exploited to develop novel chemical sensors. Metal detecting, customised organic molecules will be used to attach to the wires. Porphyrins and other active dopants will be integrated into these. The controlled self-assembly of inorganic nanoparticles is a revolution in the making. This project will involve colleagues at USyd. Optical wire magnetic composites and devices In this project the combination of silica and ferroelectric nanoparticles offers a novel tool for increasing the Faraday coefficient of silica, leading to potentially compact Faraday rotators and isolators. They will be integrated into optical waveguide form both fibre optic and planar. Single photon sources Recent work has shown the integration of nitrogen-vacancy (NV) nanodiamonds into silica is possible using nanoparticle self-assembly. Single photon emitting centres were successfully embedded. This project will attempt to fabricate practical single photon emitting source for potential quantum computing and sensing applications. The aim will be to couple these devices with optical fibres using novel approaches developed in the group that can be patented. The work will be undertaken with colleagues at RMIT. Surface patterned self-assembly This project will look at the role of patterning to direct and control deposition of drops, the self-assembly of nanoparticles and more. In particular, the integration of self-assembled nanoparticles onto silica and silicon chips will be explored. Top-down contact angle monitoring, developed in the group, will allow mapping of surface properties. Nanoparticle self-assembly inside structured optical fibres This project will examine the optimisation of novel core structures inside optical fibres to enhance functionality and allow new devices, lasers and sensors to be fabricated. With uniform porosity these structures can enable unique filtering and sieving on the nanoscale opening new ways to undertake chromatography-like sampling and probing of materials. Further reading: J. Canning, “Top up and top down: self-assembling and 3D printing custom photonic waveguides and components”, (KEYNOTE), International Conference on Emerging Advanced Nanomaterials, Newcastle Australia, (2018) and refs therein. Y. Yamada, H. Tadokoro, M. Naqshbandi, J. Canning, M. J. Crossley, S. Fukuzumi, “Nanofabrication of a solid-state, mesoporous nanoparticle composite for efficient photocatalytic hydrogen generation”, ChemPlusChem, 86 (6), 521-525, (2016) J. Canning, Laboratory-in-a-microfibre in Lab-on-fiber Technologies Springer, (ed. Cusano, Ricciardi, Consals and Crescitelli), (2014) M. Naqshbandi, J. Canning, B.C. Gibson, M. Nash, M.J. Crossley, “Room temperature self-assembly of mixed nanoparticles into photonic structures”, Nature Comm. 3, 1188 (2012) Smart device technologies Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted A number of projects exist using smart devices and smart phones to develop new and novel analytical tools capable of taking research out into the field. Due to the highly patent-sensitive nature of this work, details cannot be discussed online but inquiries from outstanding students are welcome. Smart-device diagnostics This project area will explore potential medical and agricultural applications of smart devices and photonic sensing and the internet. Smart Ophthalmology Working with the Graduate School of Health at UTS, we are developing novel smart devices for examining and diagnosing a range of disease through the eye. Software Defined Network Architecture and protocol design for Next generation Wireless networks Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Mehran Abolhasan Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Centre: Centre for Autonomous Systems Closing date: when filled Domestic and International applications accepted Over the past 10 years there has been a rapid growth and development in Wireless networking. Wireless networks have rapidly evolved over three generations reaching the current 5G wireless networking standard. 5G is seen as a major leap forward in innovation in wireless networking as it introduces higher levels of programmability and adaptability to achieve significantly better performance than 4G wireless networks. A key enabling technology in 5G is Software Defined Networking (SDN). By untangling the control and data plane from switching and routing devices, SDN enables for a more rapid innovation in the world of networking. This rapid innovation is set to accelerate the development of new generation of protocols and architectures for 5G Wireless and Beyond. However, SDN not only enables Wireless Networks to evolve quickly, but it provides the building blocks to allow them to operate much more efficiently and intelligently through the integration of AI/Machine Learning (ML) strategies. This project will investigate into how different AI/ML strategies can be used to increase the scalability, operational efficiency and security of Wireless networks. The project will seek to develop new intelligent protocols and algorithms for 5G and beyond wireless networks (including 6G). Experience Needed: Strong mathematical background, Knowledge of AI/ML, Strong knowledge of Wireless networking, Solid scripting and programming in languages such as C ++ and Python. Studying single aerosol nucleation using optical tweezers Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Professor David McGloin Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted. Ice formation in the atmosphere plays a significant role in many processes, including, for example, helping to keep the Earth cool by reflecting incoming solar radiation. A detailed understanding of the process at the single droplet level remains incomplete, however. In this project, the aim will be to develop single particle techniques to observe and probe droplet nucleation using optical manipulation and optical spectroscopy. It will involve the development of a cooling system that enables both homogeneous and heterogeneous freezing of microscopic and nanoscopic particles to be explored in a completely controlled environment. A focus will be on implementing optical manipulation techniques that can trap both transparent and opaque materials and on developing strategies to control the orientation of absorbing particles to facilitate contact nucleation studies. In parallel to this, the project will also examine freezing of bulk samples, including developing previous work on hydrocarbons and biofuel analogues, making use of Raman spectroscopy. It will also examine the ability of optical manipulation tools to explore nucleation in microfluidic environments. The project is suitable for someone with a background in physics, photonics, analytical or physical chemistry and electrical/electronic engineering and related backgrounds. The project will involve the development of the optical manipulation and spectroscopy instrumentation. Temporal anomalies in network timekeeping Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). An application for a top up scholarship is possible and fee waivers may also be considered for the successful candidate. Contact: Professor Darryl Veitch Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Centre: Global Big Data Technologies Centre Closing date: when filled Every computer on earth has a software clock on board which is essential for its own operation as well as that of applications running on it. The vast majority of these clocks are kept synchronised using a system called NTP that connects to clocks of greater accuracy over the Internet. The problem is this system has many problems, leading to incorrect timestamps, which in turn leads to software failures and likely system collapse under the weight of the Internet of Things (IoT), which will grow to trillions of devices - soon. Timekeeping is the silent Achilles Heel of many systems, for example so much of the Big Data sets now routinely collected consist of timestamps, but can we trust them? The Timing Laboratory at UTS is working to solve the research problems critical to the design of a global, networked timing system which is highly accurate, robust and reliable, and whose performance can be trusted and verified, even at the scale of the Internet of Things. It operates a state of the art timing testbed which includes an atomic clock, multiple high-end GPS receivers, and specialised timing appliances donated from leading manufacturers. In the past this project has received funding from the ARC, Google, industry-leading timing hardware manufacturer Symmetricom, and the FreeBSD Foundation, and it has a close relationship with the National Measurement Laboratory (NMI), Australia’s guardian of reference time, and its contributor to the global UTC timing standard. Temporal Anomalies in Network Timekeeping Building on the Timing Laboratory’s prior work in Server Health Monitoring (see our recent publication to see how many servers got it wrong in the end-2016 leap second event!), you will develop advanced data analytic statistical techniques, and associated computational methods, to enable anomalies/errors in timing servers to be reliably detected, even from the other side of the world. Such anomalies can lead to errors in control software in devices and can be exploited to compromise security. You will use the advanced detector to map out the anomalies in timing servers across the Internet, and you will contribute to a system - the world’s first - to expose the timing `bad guys’ to the world by working with our international research partners who control global network monitoring networks. You will also work on technology transfer on a global scale: to build server health controls into the network itself. Internships as part of the thesis work to network research centres such as CAIDA in UCSD in San Diego will be encouraged. Candidates will have a strong background in computer networking and network measurement and visualisation, programming (Matlab, Python, C), statistical analysis and data analytics. UTS CSIRO PhD scholarship Scholarship: This project includes funding for a living stipend of $22,000 per annum (tax-exempt). Fee waivers and top-ups may also be considered for the successful candidate. Contact: Dr Andrew Zhang and Associate Professor Richard Xu Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Centre: Global Big Data Technologies Center Closing date: when filled Domestic and International applications accepted Project Description: In recent years, Machine Learning has achieved phenomenal success in areas such as computer vision, natural language processing, and recommendation systems. However, its full potential is yet to be realized in many other equally important and exciting areas. In this PhD project, in collaboration with CSIRO, the prospect candidate will need to investigate and develop novel Machine Learning methodologies in “Reconfigurable metasurfaces” and the output of this research has the potential to fundamentally change network designs. Reconfigurable metasurfaces are highly desired for manipulating millimetre-wave (mmWave) or terahertz (THz) waveforms but have not been demonstrated at these very high-frequency bands. New research on mmWave/THz metasurfaces using new materials, such as nanostructured graphene, liquid crystal, and superconducting material structures. A metasurface consists of a conductive material (metallic, graphene, liquid crystal, superconductor) based pattern periodically repeated over a dielectric substrate and connected via “switching” elements. The macroscopic electromagnetic interaction of a metasurface is defined by the form of the meta-atoms and the state of the switches. A state of switches may correspond to full absorption of all waves from a direction of arrival, while another may fully reflect at a customisable angle. A highly promising material for metasurfaces is graphene, a single 2D plane of carbon atoms arranged in a honeycomb lattice, whose surface conductivity is dynamically tunable over a wide range by changing its chemical/lattice potentials through an applied DC bias voltage. The full potential of metasurfaces will be further empowered by intelligent signal processing algorithms to operate, reconfigure and control the metasurfaces to achieve real-time monitoring, decision-making and fast response. This project aims to solve the grand science challenge by designing specialised online learning techniques to capture the electrophysical characteristics of metamaterials and empower metasurfaces with. Two possible initial directions that candidate may undertake include: Direction one Signal detection has to date relied on the beam-reconfigurability of antennas or arrays. Electronic beam steering is impossible for metasurface due to the fixed material/device design and fabrication. Optically mechanical beam steering is cost-effective but at a slow scanning speed. We propose to reconfigure metasurfaces digitally and adaptively. The concept of AI/ML will be exploited to configure metamaterial switches of tiles in a decentralised manner. Specially designed learning frameworks for large-scale problems, with large state and action spaces, (such as using Reinforcement Learning with large state/action space) methodologies will develop the best Policy in order to maximize the rewards, i.e., utility of a metasurface for tracking, reflection or absorption. Direction two It is critical to have seamless transitions between smart metasurface configuration to uninterruptedly track and communicate with non-stationary (e.g., the moving platform on satellite) signal sources or destinations. The candidate can develop appropriate machine learning models to address these challenges. UTS/CSIRO partnership This is a collaborative project between UTS and CSIRO, where the candidate is expected to spend time between the two organizations. The Commonwealth Scientific and Industrial Research Organisation (CSIRO) is an Australian federal government agency responsible for scientific research. CSIRO maintains more than 50 sites across Australia and in France, Chile and the United States, employing about 5,500 people. Its notable achievements have included the invention of atomic absorption spectroscopy and essential components of Wi-Fi technology. Supervisor panel UTS A/Prof Richard Yi Da Xu (Principal): Yida.Xu@uts.edu.au A/Prof Andrew Zhang (Co-Supervisor): Andrew.Zhang@uts.edu.au CSIRO Dr Wei Ni Dr Mark Hedley Possible other members at Department of Cybernetics, Data 61, CSIRO Water photonics and future communications and sensing devices and technologies Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Professor John Canning Duration: 3 years (possible 6-month extension) School: School of Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted In recent work, Canning proposed the idea of utilising water self-assembly at interfaces as a novel electro-optic medium that can be integrated into waveguides. Even though not fully characterised and understood, the self-assembled structures can have significant Pockels effects and other interesting properties – these properties can explain anomalous results reported in 1994 of ultra-high nonlinearity in optical fibres that promised to disrupt communications. In fact the implications are tremendous and a range of possible project sexists from fundamental to applied work. A new project area that recognises for the first time the potential of water self-assembly to explain the large anomalous electro-optic effects reported in optical fibres with UV poling back in 1995 is offered. This is an exciting new medium because until now the potential for water as an opto-electronic medium has not been recognised and is ideal for an ambitious students looking to revolutionise photonics and much, much more. This new paradigm was presented at CLEO Pac Rim in Singapore in 2017 opening opportunities to collaborate with colleagues overseas. There is scope for a range of fundamental and applied projects in this field. Please contact Prof. Canning for more information. This work is suited to visionary and outstanding students looking to disrupt science and engineering in new ways. Further reading: J. Canning, “Water photonics, non-linearity and anomalously large electro-optic coefficients in poled silica fibres”, MRS Commun. 8 (1), 29-34, (2018). Wide-area urban 3D imaging Scholarship: Successful applicants will receive a living stipend and full fee waiver during both their studies in Vietnam and Australia funded through the Joint Technology and Innovation Research Centre (http://jtirc.uet.vnu.edu.vn/), a research collaboration between the University of Technology Sydney and Vietnam National University Hanoi. Contact: Stuart Perry Duration: 3 years (possible 6 month extension) School: Electrical and Data Engineering Closing date: when filled Domestic and International applications accepted. Overview: The Center for Multidisciplinary Integrated Technologies for Field Monitoring (FIMO) at the University of Engineering Technology, Vietnam National University Hanoi, together with the Perceptual Imaging Laboratory, School of Electrical and Data Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney is seeking applications from students wishing to undertake PhD studies on the topics listed below. Eligibility: Bachelors degree with honours or Masters degree in computer science, vision science or related field. Successful applicants will be expected to spend at least a year in Vietnam, studying at the University of Engineering Technology, Vietnam National University Hanoi, Vietnam, followed by a period of study at the University of Technology Sydney, Australia before returning to complete their studies in Vietnam. At the end of their studies, applicants will be awarded a PhD degree by both VNU Hanoi and UTS. To initially be accepted into the program, candidates must meet English proficiency requirement (IELTS 6.0) with demonstrated excellence in academic achievement (e.g. top venue publications). To progress to the UTS component of the program, candidates must have demonstrated research excellence during the initial stage and meet an English proficiency requirement of IELTS 6.5. The scholarship is open to all nationalities, but we encourage Vietnamese citizens in particular to apply. Successful applicants must be eligible to obtain a student visa to study in both Vietnam and Australia and be prepared to spend at least one year studying in Vietnam. Funding: Successful applicants will receive a living stipend and full fee waiver during both their studies in Vietnam and Australia funded through the Joint Technology and Innovation Research Centre (http://jtirc.uet.vnu.edu.vn/), a research collaboration between the University of Technology Sydney and Vietnam National University Hanoi. Contact Details: Please contact A/Prof Stuart Perry (Stuart.Perry@uts.edu.au) and A/Prof Thi Nhat Thanh Nguyen (thanhntn@fimo.edu.vn) to enquire about these topics. Project Description: Wide-Area Urban 3D Imaging 3D maps of urban environments are crucial for urban planning, real estate and the monitoring and prediction of environmental issues affecting cities. This project is concerned with the development of advanced urban 3D mapping technologies involving existing satellite imagery sources, and low cost drone technologies including standard camera technologies or 360 degree camera systems mounted on drones. It is envisioned that this project would involve the development of cutting edge computer vision systems involving advanced machine learning techniques. This may include machine learning to stitch 3D data from a variety of modalities or the use of machine learning to extract 3D information from satellite and 360 degree drone imagery. Wireless Power Transfer for Battery-Free Internet-of-Things Ecosystems Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,597 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Dr Wei Lin Duration: 3 years (possible 6 month extension) School: Electrical and Data Engineering Centre: Global Big Data Technologies Center Closing date: when filled Domestic and International applications accepted. The Opportunity: Two fully funded PhD Scholarships are available for outstanding candidates to work on a 3 year PhD program at the University of Technology Sydney with the Global Big Data Technology Centre investigating antennas and circuits primarily for wireless power transfer applications. The research topics will include advanced multi-functional antenna arrays that will broadcast electromagnetic energy to remote IoT (Internet of Things) elements and the ultra-compact, highly efficient rectennas that will then convert it to empower the sensor and communications functions seamlessly integrated into them. The fabrication of their prototypes and subsequent verification of their overall performance will be an integral part of the research efforts. Moreover, the adaptation of the developed arrays and battery-free IoT elements to real world application scenarios will be an important goal to demonstrate the efficacy of the consequent wirelessly powered IoT ecosystems. High quality research outcomes are anticipated during the program including papers in first rank IEEE journals. The candidates will have fully-funded opportunities to attend international and domestic conferences to present their work if their papers are accepted. Candidate Requirements: As the successful candidate, you will have outstanding academic credentials and will: • Have a strong background in Antennas and RF circuit designs • Have a bachelor’s degree with a relevant Honours or Master’s degree in any of the fields described above or an intimately related field • Meet the eligibility criteria for PhD candidature at the University of Technology Sydney • Good experience in antenna and circuit measurements, simulations, and analysis • Good knowledge and experience in the use of antenna and circuit simulation tools such as ANSYS and ADS • Strong written and spoken English proficiency Information, Systems and Modelling Building climate change knowledge Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Flavio Pileggi Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling Centre: PERSWADE Closing date: when filled Domestic and International applications accepted. Development of a knowledge-based system to support the systematic collection, analysis, organisation and communication to different stakeholders of data and information about Climate Change. The target knowledge building process will apply advanced techniques for document analysis, data integration and visualisation, conceptual modelling, as well as cutting-edge HCI methods (e.g. conversational search). The candidate should have a background in Computer Science (or related fields) with strong software development skills. Additionally, the candidate is expected to have strong interest around climate change, sustainability and social responsibility. Previous experience with ontology and document analysis may be a factor. Circular economy: Techno-economic analysis and life cycle assessment of CO2 utilisation and green chemicals within the regional Australian and global economy Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Associate Professor Kaveh Khalilpour Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling Centre: PERSWADE Closing date: when filled Domestic and International applications accepted The development of successful climate change mitigation policies requires rigorous socio-environmental and macroeconomic models. The goal of this study is to assess the impact of developing CO2 recycling industry (for the production of green chemicals) in the Australian and global economy, in terms of detrimental factors such as environmental impacts, employment, and GDP. The study will be based on the integration of life cycle analysis (LCA) and world socio-economic input-output analysis. The extended input-output analysis will enable measuring the intricate relationship of the sectors of an economic region, their respective environmental impact as well as their employment capabilities. Relevant reference Rojas Sánchez, D., Hoadley, A., Khalilpour, K. (2019), A multi-objective extended input–output model for a regional economy, Sustainable Production and Consumption, 20, 15-28, https://doi.org/10.1016/j.spc.2019.04.009. Selection Criteria - Background in life cycle analysis - Background in linear programming - Background in econometrics and macroeconomics Data analytics and optimisation to improve decision making (multiple opportunities) Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Dr Subrata Chakraborty Duration: 3 years (possible 6-month extension) School: School of Information, Systems and Modelling Closing date: when filled Domestic and International applications accepted. This project area aims to utilise and develop traditional and advanced data analytics models such as Fuzzy sets, Multiple Criteria Decision models, Agent based modelling, Bayesian modelling, deep learning models etc. to solve real world challenges. Both applied and theoretical research is of our interests. Key Project Areas: Education Analytics: Analyse various education data such as student interaction, satisfaction survey to improve education delivery. Supply Chain and Scheduling: Improving vehicle routing and scheduling for various businesses. Business Decision making: business process modelling and decision support through big data analytics. Theoretical framework: Developing and improving fundamental optimisation models. (Requires good statistical & mathematical background) Energy-water nexus: Optimal design and grid integration of renewable desalination systems Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Associate Professor Kaveh Khalilpour Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling and School of Civil and Environmental Engineering Centre: PERSWADE Closing date: when filled Domestic and International applications accepted The concurrent growth of world populations and water scarcity has led to a greater demand for water desalination systems. However, the energy intensity and subsequent high costs of desalination remain the main barrier for the widespread deployment of desalination systems. Add to this, the sustainability concerns of fossil fuel energy sources. This challenge has led to focused international research on the energy-water nexus, i.e. energy-efficient water production systems. One possible pathway in this context is the integration of desalination processes with renewable energy sources. Various renewable energies—such as solar, wind, and geothermal—can be coupled with many desalination methods, based on the availability of these resources in different locations, and also on other factors such as reliability required or the capital cost of establishment. This HDR project will focus on optimal configuration, design and integration of renewable desalination systems with the objective of least cost water production. Applicants with prior knowledge (or motivation to master) in systems optimisation are welcome to apply. Relevant reference • Rabiee, H., Khalilpour, K., Betts, J. M., & Tapper, N. J. (2019). Energy-water nexus: renewable-integrated hybridized desalination systems. In Polygeneration with Polystorage : For Chemical and Energy Hubs (pp. 409-458). London UK: Elsevier. https://doi.org/10.1016/B978-0-12-813306-4.00013-6 • Mujtaba, I, Srinivasan, R., & Elbashir, N. (2017). The Water-Food-Energy Nexus: Processes, Technologies, and Challenges. https://doi.org/10.1201/9781315153209. Selection Criteria - Background in process systems optimisation - Background in water and energy systems Energy network planning and scheduling considering renewable energies, energy storage, and uncertainties Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Associate Professor Kaveh Khalilpour Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling Centre: PERSWADE Closing date: when filled Domestic and International applications accepted Motivated by the strong market uptake of PV and wind technologies, the energy network is in an irreversible journey toward decentralisation. The energy planning objectives in this context is moving to scenarios such as "100% renewables", "net-zero emission", "net-negative emission" and "climate-neutral" networks. The key challenges are the added uncertainties including but not limited to energy supply (e.g. availability of wind/solar), demand at the prosumer era, new technology learning rates, carbon penalty, and the emergence of energy storage systems. The objective of this HDR project is to develop economic dispatch, unit-commitment, and Optimal Power Flow (OPF) frameworks for planning and scheduling of community, state, or national level energy network infrastructures. The study can consider both long-term planning and short-term scheduling. The key case-study will be the Australian National Energy Market (NEM). Relevant reference Khalilpour, K. R., & Vassallo, A. (2016). Community Energy Networks With Storage: Modeling Frameworks for Distributed Generation. (Green Energy and Technology). Springer. https://doi.org/10.1007/978-981-287-652-2 Khalilpour, KR 2019, The Transition From X% to 100% Renewable Future: Perspective and Prospective, In Polygeneration with Polystorage for Chemical and Energy Hubs, Pages 493-512, https://doi.org/10.1016/B978-0-12-813306-4.00016-1 Selection criteria - Background in mixed-integer optimisation (preferably GAMS or Gurobi) - Background in network planning - Background in energy systems, markets, and policy Explainable AI in spatial modeling of natural hazards Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dist. Professor Biswajeet Pradha Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling Centre: Centre for Advanced Modelling and Geospatial lnformation Systems Closing date: when filled Domestic and International applications accepted In this project, we aim to forecast and predict natural hazards (hydrological and meteorological hazards such as droughts, fires, mass movements – landslides, debris flows, land subsidence, floods etc.) using spatial-based explainable artificial intelligence models. The model outcomes will be interpreted using an interpretable algorithm. Although, there is an abundance of literature on using various data-driven models for natural hazard modelling and prediction, this project would introduce the use of SHapley Additive exPlanations (SHAP) in the field of spatial forecasting in natural hazards which explains the compound effect among the variables towards model outcomes. This research would be a first of its study towards interpreting the forecasting model in natural hazard based studies which could help in understanding the behaviour of natural-hazard related variables. Green supply chain framework development based on renewable hydrogen vector Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Associate Professor Kaveh Khalilpour Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling Centre: PERSWADE Closing date: when filled Domestic and International applications accepted The conventional hydrogen production pathway is fossil fuel-based, involving fossil fuel reforming for synthesis gas generation. While hydrogen itself is clean and sustainable, its dependence on fossil fuels has been the key challenge hindering its consideration as an alternative energy source. In recent years however the projection of a possible renewable energy over-supply has created a new story for the hydrogen economy, which is based mainly on water splitting, using renewably sourced energy. The interests have gone even beyond the self-security concerns and there is a growing interest in hydrogen export as a commodity which requires a full supply chain including production/generation, storage/carrier and conversion. The key advantage of hydrogen over other energy storage alternatives such as batteries is its potential for long-term, seasonal, storage at massive capacities. The lower heating value (LHV) of hydrogen is 120 MJ/kg, compared to about 50 MJ/kg for methane and even less for petroleum products. Although the LHV of hydrogen is extremely favourable, it suffers from low volumetric density (e.g., 0.0823 kg/m3 at the ambient condition). Therefore, improving the volumetric density of hydrogen is a necessary step in facilitating optimal hydrogen supply chain development. This is achievable with several options including compression, liquefaction, physisorption, and chemisorption which will be rigorously studied in this project. The project is around Integrated multi-scale design of materials, process system, and the market for building green and viable hydrogen supply chain. The successful higher degree by research (HDR) students will work on multiscale modelling of renewable hydrogen production-storage-consumption systems from computational materials synthesis to optimal system design and integration with the renewable energy market. The potential students are expected to have a good background in one or more of molecular modelling, thermodynamics, and process systems engineering, with emphasis on theoretical optimisation. Some references: · International Energy Agency (IEA), 2019, The Future of Hydrogen · Abdin, Z., Zafaranloo, A., Rafiee, A., Mérida, W., Lipiński, W., & Khalilpour, K. R. (2020). Hydrogen as an energy vector. Renewable and Sustainable Energy Reviews, 120. https://doi.org/10.1016/j.rser.2019.109620 · Khalilpour, K., Pace, R., Karimi, F. (2020) Retrospective and prospective of the hydrogen supply chain: A longitudinal techno-historical analysis, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.02.099 Selection criteria - Background in systems optimisation (preferably GAMS or Gurobi) - Background in energy systems, markets, and policy - Background in network planning Interested students, please send your letter of interest to Kaveh.khalilpour@uts.edu.au. Information, disinformation and fake news Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Flavio Pileggi Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling Centre: PERSWADE Closing date: when filled Domestic and International applications accepted Adoption of text/semantic analysis techniques to analyse news as posted by relevant mass media as well as within social networks and informal sources of information. The candidate is expected to have strong software development skills. Experience with ontology and document analysis is welcome. Image and video analytics with deep learning models for applications in multiple domains (multiple opportunities) Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Subrata Chakraborty Duration: 3 years (possible 6-month extension) School: School of Information, Systems and Modelling Closing date: when filled Domestic and International candidates accepted. This focus of this project area is to develop deep Learning models such as Convolutional neural networks (CNN) models capable of performing image and video analysis including classification, segmentation, detection etc. Key technology and tools to be used include Python, MATLAB, Keras, TensorFlow, AWS etc. Key project areas: Medical image analysis: Disease detection and classification (such as Lung Cancer detection) from X-Ray, CT and MRI scans. Agricultural image analysis and GIS: Identifying different diseases and insect infestations and crop health monitoring in specific crops such as cotton and grapes. Video analysis: Video summarisation, action, event and emotion detection in video samples. Visual Attention Modelling: Eye Tracking based human visual attention modelling. Improving deep and machine learning using second-order information Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Dr Subrata Chakraborty Duration: 3 years (possible 6-month extension) School: School of Information, Systems and Modelling Closing date: when filled Domestic and International applications accepted. University of Technology Sydney – City campus. UTS is #1 young university in Australia in 2019 based on QS and THE ranking. Also, UTS is ranked #29 globally and #1 in Australia for the subject area of Computer Science and Engineering (based on 2019 ARWU rankings) This project is about incorporating second-order information into machine learning methods in order to boost the initialization and learning processes. From the machine learning methods in this project, it particularly focuses on deep neural networks. Several topics are going to be investigated in this project including hybrid approaches, big data analytics, graph theory, large scale problems. A solid background in data and computer sciences as well as strong programming skill (MatLab/Python). A master degree in data science, computer science, mathematics, AI, engineering, or related field. Background in statistics and machine learning methods, deep learning in particular. Publications with major conferences and/or journals. Integrating physical and machine learning models in spatial hazard assessment Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dist. Professor Biswajeet Pradha Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling Centre: Centre for Advanced Modelling and Geospatial lnformation Systems Closing date: when filled Domestic and International applications accepted Reliable prediction of natural hazards is essential for risk mitigation which can reduce fatalities and economic losses. Physical and machine learning models are the common approaches for assessing natural hazard modellings. For examples, in mass movements, the physical-based model combines susceptibility analysis with soil and rock mechanics, establishing a physical basis for this method. It is a suitable method at a local-scale and requires site-specific geotechnical information. Nevertheless, a machine learning model uses historical landslides (inventories) and conditioning factors through machine learning algorithms. This method is appropriate for regional-scales; however, the availability of adequate training data/inventories and explainability are the main limitations of this method. These two approaches, in fact, complement each other. The physical-based model is interpretable and offers the capability of extrapolation beyond observed conditions. In contrast, machine learning approaches are highly flexible for data adaptation. The project covers integrated physical and machine learning models for explainable spatial landslide prediction and early warning. The topics of interest include, but not limited to: • Designing and developing explainable landslide susceptibility models. • Evaluating and improving common physical and machine learning landslide prediction models. • New methodologies for integrated landslide susceptibility modellings. • Integrated physical models for landslide predictions. • Explainable landslide deep learning/machine learning modellings. • Susceptibility assessment and mapping, spatial statistics, and visualization of integrated sensors, data, and information. • Applications of multi-source remote sensing data and information fusion for landslide modelling. • Landslide detection and monitoring. " Probabilistic demand and price forecasting with micro- and macro-economic factors Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Associate Professor Kaveh Khalilpour Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling Centre: PERSWADE Closing date: when filled Domestic and International applications accepted Often demand and price forecasting techniques are developed for short-term scheduling purposes with consideration of micro-economic inputs. However, in medium- and long-term planning macroeconomic parameters also play important roles. The goal of this project is to develop efficient probabilistic forecasting algorithms for medium- and short-term (energy) demand and price projection with consideration of macroeconomic parameters and mixed-frequency data. Applicants with prior knowledge (or motivation to master) in data analysis are welcome to apply. Relevant reference - Lusis, P., Khalilpour, KR., Andrew, L., & Liebman, A. (2017). Short-term residential load forecasting: Impact of calendar effects and forecast granularity. Applied Energy, 205, 654-669. https://doi.org/10.1016/j.apenergy.2017.07.114 - Khalilpour, KR., & Vassallo, A. (2016). Community Energy Networks With Storage: Modeling Frameworks for Distributed Generation. Springer. https://doi.org/10.1007/978-981-287-652-2 Selection Criteria - Background in data analysis, particularly predictive analytics - Background in econometrics Remote sensing data and its Applications Using AI Techniques and Explainability based models Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dist. Professor Biswajeet Pradha Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling Centre: Centre for Advanced Modelling and Geospatial lnformation Systems Closing date: when filled Domestic and International applications accepted This project will focus on the development of artificial intelligence based models for several environmental applications included but not limited to natural hazard management, urban planning and urbanisation problems. The availability of higher resolution images captured from UAV has provided new directions in several fields, and therefore there is a need to build more robust and advanced AI based models. These models should provide better solutions to existing environmental issues ranging from developing novel architectures and its optimization to explaining the model outcomes. UAV based AI models have the benefit of automatic processing owing to shorter temporal resolution which would learn from historic experiences and provide solutions to the fast-changing environment and goals. The tasks in UAV-AI system are interesting, and each being valuable in a specific domain, with an aim to better explain the model results, and providing a reasonable explanation of the results, thereby achieving the ultimate goal of Explainable AI. There is a growing need for UAV imaging platform including image types like hyperspectral, multispectral, LiDAR and several others including AI technologies like machine learning, specifically, deep neural networks, knowledge graphs, neurofuzzy models, along with optimization techniques, such as genetic algorithms, particle swarm optimization, firefly algorithms etc., for decision-making and modelling purposes. The application areas to be considered as following: • Multispectral/hyperspectral image processing for environmental problems; • Time series analysis for short- and long-term change detection in disaster monitoring and environmental monitoring; • Power line monitoring; • Target detection for forest fire mitigation; • Multispectral/hyperspectral image processing for agricultural monitoring; • Anomaly detection like suspicious detection; • Water/air pollution monitoring. Robustness analysis of energy networks against cascading failure Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Associate Professor Kaveh Khalilpour Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling Centre: PERSWADE Closing date: when filled Domestic and International applications accepted Cascading failure of infrastructure networks incurs substantial economic and social consequences. As such, there are intensive research activities on improving infrastructure networks resilience. The robustness of the Australian national energy network has been also questioned on several occasions such as the Basslink failure in 2015 and South Australia blackout in 2016. The core aim of this project is to develop efficient methodologies for assessing the reliability of networks with consideration of dependent failures. The study will assess various case-studies including the Australian electricity and gas networks to identify the critical nodes which make these networks susceptible to failure (physical or cyber-attack). Selection criteria - Background in network (graph) theory - Background in programming (preferably Matlab, or R, or Py) - Ability to work with GIS data Tariff fairness: Optimal utility tariff design in the decentralised network context Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Associate Professor Kaveh Khalilpour Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling Centre: PERSWADE Closing date: when filled Domestic and International applications accepted It is long known that the peak demand accounts for over-investment in the utility (e.g., electricity, gas, and water) network assets. This results in a high price of delivered utility which does not fairly differentiate between peak and non-peak users. Utility tariff is proven to be one of the best demand-side management (DSM) tools for shaping consumers’ behaviour. Still, the mainstream pricing models are inclining block and time-of-use tariffs and other mechanisms are less discussed or practised. The objective of this HDR research project is to utilise optimisation formulations and data analytics for evaluation of the impact of current tariffs in terms of fairness and justice for consumers. The main research query will be how to introduce tariff mechanisms which direct the peak-consumers behaviour toward taking more responsibility in their peak demand management. Such solutions not only can improve the resilience of the utility networks but also can contribute to social fairness by avoiding the transfer of the associated costs of peak demand to all users. Especial attention will be given to the case of decentralised electricity networks in the context of energy-justice nexus. Relevant reference - Khalilpour, KR & Lusis, P 2020, Network capacity charge for sustainability and energy equity: A model-based analysis, Applied Energy, vol. 266, pp. 114847-114847. https://doi.org/10.1016/j.apenergy.2020.114847 - Zhong, Q., Khalilpour, R., Vassallo, A., & Sun, Y. (2016). A logic-based geometrical model for the next day operation of PV-battery systems. Journal of Energy Storage, 7, 181-194. https://doi.org/10.1016/j.est.2016.06.008 Selection Criteria - Background in data analysis and optimisation - Background in network analysis - Background in energy systems, markets, and policy Virtualised cooperative peer-to-peer energy markets Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Associate Professor Kaveh Khalilpour Duration: 3 years (possible 6-month extension) School: School of Information Systems and Modelling Centre: PERSWADE Closing date: when filled Domestic and International applications accepted With the widespread emergence of microgrids, virtualised smart energy networks are being developed and new Energy Services Company (ESCO) business models are evolving with the role of power aggregator. These businesses can operate in either in centralised form or create virtual smart energy networks where small, medium and major energy prosumers could be able to sell/buy energy amongst themselves as well as with the involvement of centralised aggregators. The goal of this study is to design advanced cooperative peer-to-peer market models (cooperation, selfishness, games, auction, etc.) with a focus on scheduling policies (optimal sell/buy/store decisions) for the cooperation of multiple microgrids in larger coalitions. The study will also investigate the role of various generation (PV, wind, Genset, etc.) and storage (battery, hydro, hydrogen, etc.) systems in virtual markets. Relevant reference • Khalilpour, KR 2019, Design and Operational Management of Energy Hubs: A DS4S (Screening, Selection, Sizing, and Scheduling) Framework, In Polygeneration with Polystorage for Chemical and Energy Hubs, Pages 493-512, https://doi.org/10.1016/B978-0-12-813306-4.00015-X. • Khalilpour, KR & Vassallo, A 2016, Noncooperative Community Energy Networks, DOI: https://doi.org/10.1007/978-981-287-652-2_8 • Khalilpour, KR & Vassallo, A 2016, Cooperative Community Energy Networks, DOI: https://doi.org/10.1007/978-981-287-652-2_9 Selection Criteria - Background in mixed-integer optimisation (preferably GAMS or Gurobi) - Background in network analysis - Background in energy systems, markets, and policy Mechanical and Mechatronic Engineering Additive manufacturing (3D printing) toolpath optimization Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Mickey Clemon Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic candidates only. Additive manufacturing needs control algorithms and toolpath planning methods that allow for omnidirectional fabrication. This project explores various methods of control to achieve this goal. Topics: Optimization of single and multi-point extrusion deposition of material in additive manufacturing Optimization of single and multi-point spray deposition of inks in additive manufacturing Toolpath planning for 4+ axis deposition Line-based deposition design and control Additive manufacturing of fibrous composites for topologically optimised structures Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Mickey Clemon Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic applications only. Fibre reinforced composite structures can greatly alter the material properties of a bulk matrix material. The induced anisotropic behaviour can be advantageous for loads aligned with the fibres. This project explores the control of chopped fibre reinforce composite fabrication through additive manufacturing (3D printing), and the use of that information in topology optimised structures. Advancing Australia’s industry – Uptake of Industry 4.0 in Australian SMEs Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Matthias Guertler Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic candidates only. This research project will explore how Australian SMEs (small- and medium-sized enterprises) can be supported in successfully taking up Industry 4.0. Industry 4.0 describes the radical transformation of modern manufacturing systems using new manufacturing as well as information and communications technologies (ICT). While new sensors, software systems and AI allow for the development of digital twins as the basis of cyber-physical systems, which can be used to visualise, flexibly manage and predict physical systems and their behaviour, internet of things technologies allow for connecting manufacturing and organisational systems across entire value-chains. In addition, additive manufacturing and cobots allow for new manufacturing highly customised and novel products. However, the use of Industry 4.0 has been limited in SMEs. This applied research project will empirically explore how Australian SMEs are approaching Industry 4.0. This includes companies using Industry 4.0 and those still thinking about adopting it. Therefore, the research project will analyse company’s experience of adopting Industry 4.0 including positive experience, challenges, barriers, and strategies to approach them as well as concerns and barriers preventing companies from using Industry 4.0. The expected outcome is a framework of success factors, barriers and best-practice examples that can help companies to successfully approach and use Industry 4.0. This research project will be in collaboration with UTS Rapido, which together with the School of Mechanical and Mechatronic Engineering will provide a sufficient portfolio of industry projects to analyse and to evaluate findings. The successful candidate will be part of the new UTS Advanced Manufacturing research group with a partner institute at the Technical University of Dortmund, Germany, allowing for close collaboration and exchange with academics and other HDR/PhD students. Through existing contacts to the NSW Department of Industry and the NSW Treasury, this research project also has the potential for high visibility and contribution to the “NSW advanced manufacturing industry development strategy”. Depending on the candidate’s performance and topical fit, there is also the opportunity to work as research assistant on selected industry research projects. All candidates should have: Excellent master’s degree or bachelor’s degree with honours in mechanical/manufacturing engineering, engineering design, engineering management or a related area from the engineering or innovation management field Excellent written and spoken English Willingness to actively contribute to a thriving academic environment as an active member of the UTS Advanced Manufacturing research group Ability to work independently as a researcher and effectively in a team. Experience of working in or with industry is an advantage Archaeonics – Using ancient knowledge and solutions to solve modern problems in a sustainable way Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Matthias Guertler Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic candidates only. Humans have been innovating for thousands of years leading from radical innovations like the wheel to contemporary ones like additive manufacturing and Industry 4.0. Although there is an awareness of the achievements of previous generations on a general level, a common problem of innovation projects is that existing solutions are neglected and the “wheel is re-engineered” repeatedly. For instance, often working solutions become obsolete due to technological or societal advancements, so later after a couple of further advancements, they are widely forgotten although there core concepts would be relevant again. However, over the past years a new approach called “archaeonics” (archaeology + techniques) focuses on exploring ancient and other forgotten solutions and their benefits for modern problems. Examples include ancient agriculture approaches for exposed regions, building materials with specific temperature insulation properties and Roman water infrastructure approaches to support cistern building project in Africa as well as a raising awareness of Indigenous fire management approaches to prevent Australian bushfires. Although archaeonics could principally be used for any kind of innovation project, it appears to be particularly powerful for low-tech projects. It shows a great potential especially for “frugal innovation” and developing robust solutions that can be realised and maintained with simple tools and locally available resources. Therefore, it contributes directly to overarching trends like increased sustainability. A current key challenge of archaeonics is the identification of suitable ancient/previous solutions and their efficient mapping to modern problem. So far, the process is mainly experienced-based. To close this gap, the goal of this engineering design research project is the development of a methodology (methodical guideline) that helps to map solutions and problems – from a solution-push as well as problem-pull perspective. Along with a systematic literature review of existing archaeonics and related case studies, key activities include the development of a framework to describe ancient solutions and modern problems in a systematic way. Based on this, a systematic mapping and selecting method will be developed. Potential collaboration with, for instance, Engineers without Borders will allow for applying, evaluating and enhancing the new archaeonics methodology. This research project is at the interface of engineering, design, archaeology and cultural studies. So, an appetite for discipline-spanning collaboration is important. All candidates should have: Excellent master’s degree or bachelor’s degree with honours in mechanical engineering, engineering design, or a related area from the engineering, design or innovation management field Excellent written and spoken English Willingness to actively contribute to a thriving academic environment as an active member of the UTS Advanced Manufacturing research group Ability to work independently as a researcher and effectively in a team. Bio-inspired four-limb robots for climbing complex truss structures Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Up to $15,000 top-up per annum is available for outstanding candidates. Contact: Distinguished Professor Dikai Liu School: School of Mechanical and Mechatronic Engineering Centre: Centre for Autonomous Systems Closing date: when filled Domestic and International applications accepted The project involves the development of intelligent robots for climbing and maintaining truss structures such as electric power transmission towers and telecommunication towers. These truss structures vary significantly in size, shape and structural complexity with dense and sparse beams at different heights. The robot is expected to autonomously scan its environment and understand what it has sensed, decide where to move to next and how to move to there, and interact with a structural member with the cleaning and painting tool. This research will conduct analysis and modelling of human motion in climbing complex truss structures, develop methods that represent spatial, temporal and causal relationship, and then develop algorithms for mission planning. Machine learning will be applied for robot learning from human climbing demonstration. Boosting advanced product life-cycle management through Industry 4.0 Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Matthias Guertler Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic candidates only Industry 4.0 describes the radical transformation of modern manufacturing systems using new manufacturing as well as information and communications technologies (ICT). While new sensors and software systems allow the development of digital twins as the basis of cyber-physical systems, which can be used to visualise, flexibly manage and predict physical systems and their behaviour, internet of things technologies allow for connecting manufacturing and organisational systems across entire value-chains. The combination of advanced sensors and data analytics allow for predicting system evolutions like required maintenance as well as for identifying aspects to be improved for a following system’s generation. This also allows for great opportunities and benefits for an improved life-cycle management of products and systems. Improving a manufacturing system through updates and upgrades, redesigned processes and additional services can significantly increase system performance, reduce energy/resource consumption and enhance a system’s lifetime – which therefore directly contributes to a trend of increasing sustainability. Therefore, this applied research project will focus on exploring and analysing the link between Industry 4.0 and system life-cycle management. Exemplar questions include: What are characteristics and issues in different life-cycle phases? How could different Industry 4.0 technologies and approaches address these issues? How can this, for instance, enable improvements of existing systems and processes including predictive activities, and the development of upgrades and complementary services. An important aspect is also how to engage different stakeholder groups in terms of open innovation to use their expertise to contribute to improving each phase of a system’s life-cycle. Depending on the selected focus (product versus manufacturing system), the successful candidate has the opportunity to work with the UTS Industrial Algae Reactor (one of Australia’s selected Industry 4.0 Test Labs). Depending on the candidate’s performance and topical fit, there is also the opportunity to work as research assistant on selected industry research projects. The successful candidate will be part of the new UTS Advanced Manufacturing research group with a partner institute at the Technical University of Dortmund, Germany, allowing for close collaboration and exchange with academics and other HDR/PhD students. All candidates should have: Excellent master’s degree or bachelor’s degree with honours in engineering design, mechanical/manufacturing engineering, engineering management or a related area from the engineering or innovation management field Excellent written and spoken English Willingness to actively contribute to a thriving academic environment as an active member of the UTS Advanced Manufacturing research group Ability to work independently as a researcher and effectively in a team. Experience of working in or with industry is an advantage Bringing additive manufacturing to Australian industry Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Matthias Guertler Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic candidates only. Additive manufacturing (“3D printing”) is a powerful technology in the suite of advanced manufacturing/Industry 4.0 technologies. Exemplar benefits include the manufacturing of small customised solutions as well as the realisation of complex designs that could not or hardly be manufacturing with traditional manufacturing technologies. Therefore, additive manufacturing is a highly promising technology for Australian SMEs to increase the variety and functionality of their product portfolios and get more independent from international supply chains. Despite these benefits, companies, SMEs in particular, are hesitant to implement and use additive manufacturing. Key issues include that companies do not know where to start, what machine to buy, how to embed them into their organisation and how to effectively use them. Therefore, this research topic focuses on developing a methodical guideline (methodology / heuristic) that guides companies through the implementation process of additive manufacturing. Relevant aspects include the analysis of the current company capabilities and future needs, mapping them to different additive manufacturing systems to identify the most suitable ones, identification how the selected systems need to be tailored to each company and what preconditions companies need to realise in order to use the new system successfully, such as required (CAD) software systems, trainings, interfaces to other processes etc. Aside from using relevant literature, this research project will use several UTS-industry research projects on additive manufacturing through a multi-case study approach. This includes the retrospective analysis of finished projects as well as the participation in running projects. The latter also allows to evaluate and refine the new methodical guideline. This research project will be in collaboration with UTS Rapido, which together with the School of Mechanical and Mechatronic Engineering will provide a sufficient portfolio of industry projects to analyse and to test the new guideline. Through existing contacts to the NSW Department of Industry and the NSW Treasury, this research project also has the potential for high visibility and contribution to the “NSW advanced manufacturing industry development strategy” Depending on the candidate’s performance and topical fit, there is also the opportunity to work as research assistant on selected industry research projects. All candidates should have: Excellent master’s degree or bachelor’s degree with honours in mechanical/manufacturing engineering, engineering design, engineering management or a related area from the engineering or innovation management field Excellent written and spoken English Willingness to actively contribute to a thriving academic environment as an active member of the UTS Advanced Manufacturing research group Ability to work independently as a researcher and effectively in a team. Experience of working in or with industry is an advantage Building a Global Industry 4.0 Brewery Production Network between UTS and Germany Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Matthias Guertler Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic candidates only. The PhD project will directly work with and contribute to the new Industry 4.0 nano-brewery at the UTS Centre for Advanced Manufacturing (CAM). The overarching goal is developing a global cyber-physical production network through building a digital twin and connecting the CAM brewery with its identical physical twin at our partner institute at the Technical University of Dortmund, Germany. A specific research focus is on the development of smart recipes and associated machine learning prediction models. These, for example, allow the exchange of beer recipes across different production sites and an automated brewery system adjustment to changing ingredient qualities to ensure a stable process and outcome quality. The industry-usability and transferability will be evaluated as part of our partnership with the local award-winning brewery Young Henrys. The scope of the overarching research program allows for different angles and scopes of the PhD project, for example ranging from development of prediction models for smart recipes and their transfer between brewery systems to exploration of business implications of smart recipes, such as impact on product development practices and new business model opportunities. The PhD will offer the opportunity to develop a project that has industry relevance and that allows to be part of a collaborative initiative across different countries. The PhD project will be part of a larger research initiative and team of the Centre for Advanced Manufacturing (CAM) at UTS and the Institute of Production Systems at TU Dortmund. This provides the PhD with the unique opportunity to work within a team of peers as well as experienced researchers. It is envisioned that the PhD enrols at UTS, with the possibility of an extensive research stay at the Technical University of Dortmund, Germany. Desired qualifications and skills We expect you to have a combination of some of the following skills: Expertise and prior experience in e.g. industrial data science, engineering design, production engineering Competences in (industrial) data science and advanced methods for data collection Programming skills Experience in working with or in industry and interdisciplinary teams Excellent master’s degree or bachelor’s degree with honours in engineering management, mechanical engineering, or a related area from the engineering or management field Excellent written and spoken English Willingness to actively contribute to a thriving academic environment Ability to work independently as a researcher and effectively in a team Willingness to participate in a brewery training and support the operation of the CAM brewery Complex dynamics in biotremology Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). An application for a top up scholarship is possible and fee waivers may also be considered for the successful candidate. Contact: Dr Sebastian Oberst Duration: 3 years (possible 6-month extension) School: School of Computer Science and School of Mechanical and Mechatronic Engineering Centre: Centre of Audio, Acoustics and Vibration Closing date: when filled Domestic and International applications accepted If interested, please contact Dr Sebastian Oberst by sending him an email contacting a motivation letter and CV together with relevant diploma, transcripts, publication list and contact details of two referees. The Centre for Audio, Acoustics and Vibration (CAAV) was formed in 2017 and now has nine full time academic staff. The Centre is based at Tech Lab, which is a brand new research led facility that is close to the airport in Sydney. Tech Lab hosts brand new state-of-the-art acoustics experimental facilities that includes an anechoic chamber, semi-anechoic chamber, reverberation room and sound transmission loss suite. These new facilities will support new research projects in acoustics, including this current project. Termites communicate mainly over vibrations transmitting and receiving miniscule wave packages, which travel along wood fibres and termite-built clays. Our research in the past indicated that it should be possible in principle to use vibration signals to determine an individual ants’ or termites’ location (vibroklinotaxis). We were the first who evidenced termites substitute wood by building load-bearing structures. While past research has been focused either on the sender or the receiver, individual or groups of termites, the properties and the function of the substrate as food, communication channel or building materials has been neglected. The project aims at studying structures of the higher and lower termites. Different structures of within the mound and close to foraging sites are collected from nature reserves (Darwin, Canberra). Mounds of different colonies will be dissected and the material specimen will be taken out, analysed using micro-CT and mass spectroscopy. The static and dynamic material properties need to be experimentally and statistically analysed. The material features will be clustered using machine-learning techniques, 3D recurrence quantification and recurrence networks and matched with geometry. Using a computer model, vibro-acoustic simulations will be conducted to explore the role of transfer paths in vibroklinotaxis. The successful candidate will work in a thriving acoustics research group at a brand new facility dedicated to impactful research and which will include the chance to collaborate with researchers in other areas at Tech Lab, as well as undergo research training and development. Findings are expected to contribute to the understanding how termites build and whether different functions and properties can be assigned to different parts of their structures. Novel bio-inspired acoustic porous materials are likely to be innovated by this research – with huge potential for technology transfer. The successful candidate holds a MSc/MEng degree either in physics, applied mathematics, theoretical mechanics and materials engineering (with an interest to work interdisciplinary). Skills in mathematics, especially statistics and machine learning are required. Knowledge of nonlinear dynamics and nonlinear time series is not expected but desired. Excellent command of English is necessary and communications as well as presentation skills are important. The project is suitable to candidates who have a solid background in experimental vibration testing and transfer path analysis as well as signal processing methods. A potential candidate also requires good knowledge of statistics and numerical modeling and should be interested in working with insects and insect structures. Some travel and fieldwork will be required. Composite material design for additive manufacturing Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Mickey Clemon Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic applications only. Materials used in additive manufacturing should be designed for the nuances of the process rather than copied from wrought materials. This project explores the full space of metals, ceramics, and polymers to facilitate design of materials that fully utilise the manufacturing process. Topics: Computational design of composite materials that leverage the advantages of additive manufacturing Multi-material deposition characterization Multi-material design methodologies Sensor fabrication from mixed materials. How an Open Innovation Network can foster collaboration across the Australian Cobot Centre Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Matthias Guertler Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic candidates only. The applied PhD project will be in the context of the new ARC Australian Cobot Centre, a new joint 5-year research centre to research and foster the use of collaborative robots (“cobots”) in Australian companies. Partners aside from UTS include QUT, Swinburne and six industry partners. Given the number of partner organisations, the number of university and industry researchers and the 5-year duration, enabling successful collaboration and knowledge exchange across partners is not trivial but requires a systematic approach. Therefore, the ACC will include a so-called Open Innovation Network, which enables collaboration and knowledge exchange within the ACC as well as with associated external partners and the broader industry and government environment. The PhD program fits within the ACC and it offers the chance to directly engage with the Open Innovation Network and the numerous partners involved. This represents a unique opportunity to be part of a project that has industry relevance and that allows to build a network that extends beyond the academia at the same time. The PhD will focus on Open Innovation and how to provide a key contribution to efficiently managing the Open Innovation Network, including successful structures, processes, tools and events. Aside from planning and implementing these aspects, their application and performance will be evaluated and might lead to iterative adjustments if necessary – based on a systematic action research approach. For that reason, the PhD project requires frequent and on-going collaboration with all university and industry partners of the ACTS. It is envisioned that the PhD enrols at UTS, with the possibility of an extensive research stay at our ACC partner universities. At UTS, the PhD student will be a member of the UTS Centre for Advanced Manufacturing and play an active role within a dynamic team of peers as well as experienced researchers. Desired qualifications and skills We expect you to have a combination of some of the following skills: Expertise and prior experience in e.g. open innovation, engineering design, innovation management or collaborative project management Excellent research skills: qualitative preferred but quantitative angle possible Applied research skills, such as action research and engaged scholarship Experience in working with or in industry and interdisciplinary teams Excellent master’s degree or bachelor’s degree with honors in engineering management, mechanical engineering, design, innovation management or a related area from the engineering, design or management field Excellent written and spoken English Willingness to actively contribute to a thriving academic environment Ability to work independently as a researcher and effectively in a team Human-Robot Collaboration: trust modelling and shared control Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). An application for a top up scholarship is possible and fee waivers may also be considered for the successful candidate. Contact: Distinguished Professor Dikai Liu Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Centre: Centre for Autonomous Systems Domestic applications only Combing the strength of humans with the strength of robots provides a new way of automating tasks that are labour intensive and cannot be fully automated by the currently available technologies. Example tasks include assembly or heavy object handling in field environments. Human in the task execution loop is still needed or preferred. This research will investigate a framework and effective methods for optimal combination of strengths from both humans (e.g. perception, quick and intuitive thinking and acting, uncertainty handling) and robots (e.g. power, speed, accuracy and data-based decision-making). It will also develop performance models for predicting human co-worker’s performance in real time human-robot collaboration. Based on the performance models, a model for measuring robot trust in its human co-worker will be developed. Then shared control methods will be developed to achieve shared autonomy in human-robot collaboration. The developed models and methods will be verified in practical industrial applications. Mobile Physical Human-Robot Collaboration Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Marc Carmichael Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic applications only This project focuses on the development of novel robotic methods to provide physical assistance to humans in a variety of activities. Robots such as collaborative manipulators (cobots) can work alongside and physically assist humans. Novel control methods are needed to make this interaction intuitive and result in physical benefit for the user in the task being performed. A mobile cobot faces additional challenges due to the increased complexity that comes with the robot being able to manoeuvre its environment. This project will investigate, develop and evaluate new methods for the realisation of mobile collaborative robots and their benefits in a variety of real-world applications. The candidate ideally would have a background in mechatronics, control systems and programming. Favourable experience includes robotics and ROS (www.ros.org). As this project is not funded, the applicant would need to apply for an RTP scholarship or similar (https://www.uts.edu.au/sites/default/files/2021-04/GRS-Research-Training-Program-Scholarship-RTPS-Conditions-of-Award-2021.pdf). Natural porous vibro-acoustic media Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). An application for a top up scholarship is possible and fee waivers may also be considered for the successful candidate. Contact: Dr Sebastian Oberst Duration: 3 years (possible 6-month extension) School: School of Computer Science and School of Mechanical and Mechatronic Engineering Centre: Centre of Audio, Acoustics and Vibration Closing date: when filled Domestic and International applications accepted If interested, please contact Sebastian Oberst by sending him an email contacting a motivation letter and CV together with relevant diploma, transcripts, publication list and contact details of two referees. The Centre for Audio, Acoustics and Vibration (CAAV) was formed in 2017 and now has nine full time academic staff. The Centre is based at Tech Lab, which is a brand new research led facility that is close to the airport in Sydney. Tech Lab hosts brand new state-of-the-art acoustics experimental facilities that includes an anechoic chamber, semi-anechoic chamber, reverberation room and sound transmission loss suite. These new facilities will support new research projects in acoustics, including this current project. Termites communicate mainly over vibrations transmitting and receiving miniscule wave packages, which travel along wood fibres and termite-built clays. Our research in the past indicated that it should be possible in principle to use vibration signals to determine an individual ants’ or termites’ location (vibroklinotaxis). We were the first who evidenced termites substitute wood by building load-bearing structures. While past research has been focused either on the sender or the receiver, individual or groups of termites, the properties and the function of the substrate as food, communication channel or building materials has been neglected. The project aims at studying structures of the higher and lower termites. Different structures of within the mound and close to foraging sites are collected from nature reserves (Darwin, Canberra). Mounds of different colonies will be dissected and the material specimen will be taken out, analysed using micro-CT and mass spectroscopy. The static and dynamic material properties need to be experimentally and statistically analysed. The material features will be clustered using machine-learning techniques, 3D recurrence quantification and recurrence networks and matched with geometry. Using a computer model, vibro-acoustic simulations will be conducted to explore the role of transfer paths in vibroklinotaxis. The successful candidate will work in a thriving acoustics research group at a brand new facility dedicated to impactful research and which will include the chance to collaborate with researchers in other areas at Tech Lab, as well as undergo research training and development. Findings are expected to contribute to the understanding how termites build and whether different functions and properties can be assigned to different parts of their structures. Novel bio-inspired acoustic porous materials are likely to be innovated by this research – with huge potential for technology transfer. The successful candidate holds a MSc/MEng degree either in physics, applied mathematics, theoretical mechanics and materials engineering (with an interest to work interdisciplinary). Skills in mathematics, especially statistics and machine learning are required. Knowledge of nonlinear dynamics and nonlinear time series is not expected but desired. Excellent command of English is necessary and communications as well as presentation skills are important. The project is suitable to candidates who have a solid background in experimental vibration testing and transfer path analysis as well as signal processing methods. A potential candidate also requires good knowledge of statistics and numerical modeling and should be interested in working with insects and insect structures. Some travel and fieldwork will be required. Nonlinear energy harvesting and vibration suppression Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Dr Liya Zhao Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic and International applications accepted The project is on smart structures and systems for vibration suppression (metastructures, adaptive structures with composite smart materials) and small-scale piezoelectric energy harvesting. Requirement: Experiences in vibration, nonlinear dynamics, finite element modeling, aerodynamics, programming (e.g., matlab) and experiments are highly desired; GPA: Master's or Bachelor's degree with first- or second-class honors (>4.0/5.0). Progressing advanced manufacturing processes (such as 3D printing & manufactured products) with Laser Doppler Vibrometry (LDV) Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt). Fee waivers may also be considered for the successful candidate. Contact: Dr Ben Halkon Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic and International applications accepted. Laser Doppler vibrometry (LDV) is now readily accepted as an alternative technology for the measurement of surface vibrations with special benefits for a wide range of applications. Additive manufacturing, or 3D printing, has seen incredible interest in recent years and, with advances in processes, offers exciting opportunities. Functionally graded components, with mass and stiffness effectively placed where required, can be engineered in order that they possess specific dynamic, in addition to other, characteristics. Manufacturing components in an efficient but precise manner is clearly of critical importance. This project will investigate the application of LDV to the advancement of additive manufacturing processes in general. Specifically, the project will investigate (i) the dynamics of 3D printer systems and the impact on the quality of the finished product as a result of print head vibrations for increased print throughput rates; (ii) the possibilities for the research and development of functional components with specific vibration characteristics; (iii) the automated determination of suitability of additive/advanced manufactured components and systems on the basis of their dynamic characteristics. Realising topology optimised structures through additive manufacture Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Paul Walker Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Centre: Centre for Audio, Acoustics and Vibration Closing date: when filled Domestic candidates only. Structural topology optimisation is a computational design methodology that seeks to create complex high performing (i.e. low mass to strength ratio) structures that are impossible to realise through traditional manufacturing techniques. This project will seek to fill the missing link between Topology optimisation and additive manufacture through developing techniques around the integration of topology optimisation and additive manufacture. Working across the Centre for Audio Acoustics and Vibration and the Centre for Advanced Manufacturing, this project is seeking a capable and active student to work on application of topology optimisation to problems in vibration, vibration isolation and related fields to produce novel meta-structures that can be realised through additive manufacture. Ideally you will come from a background in mechanics, mechanical engineering, materials or mathematics and be interested in working on projects around 3D printing, mechanical design and optimisation. You will work with leading researchers in the areas of dynamics, optimisation and additive manufacturing, and have access to state of the art 3D printing facilities, including Optomec LENS – a hybrid additive manufacture and 5-axis mill – capable of integrated printing and CNC milling processes, to deliver optimised solutions with real world applications. Robotic Co-worker for Package Handling Scholarship: UTS Scholarship Scheme – Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Distinguished Professor Dikai Liu School: School of Mechanical and Mechatronic Engineering Centre: Centre for Autonomous Systems Closing date: when filled Domestic and International applications accepted The number of package deliveries significantly increases as more and more consumers continue to shop online and utilize quick (e.g. same-day) shipping options. This has created a critical issue in package handling, i.e. OH&S of package handlers. Assistive robotics allows human and robot directly work together, in flexible ways and with/without physical contact, to do a task and achieve shared goals. This project will develop methodologies and a prototype collaborative robot for unloading packages in the express process of a company. Self-lubricating gears and bearings Scholarship: Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contacts: Dr Mickey Clemon or Paul Walker Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic candidates only. The design flexibility of additive manufacturing allows for self-lubricating and internally cooled structures. This project investigates the design and performance of these structures in gearing, sliding, and rolling applications. Thermoelectric energy harvesting Scholarship: This project includes funding for a living stipend scholarship at the Research Training Program rate of $28,092 per annum (tax-exempt) with fee waivers provided. Opportunities for funding to top-up the stipend will be available across the 3 years. Contact: Dr Nick Bennett Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic candidates only. We are seeking to fill two positions appropriate for ambitious and motivated candidates wishing to carry out PhD research in experimental thermoelectric energy harvesting. Applicants should have Australian domestic student status and a high-scoring Bachelor’s/Master’s degree in an engineering subject, preferably Electronic, Electrical, Mechanical, Mechatronic or Biomedical Engineering. An interest and experience in thermoelectrics would be a distinct advantage. About the Projects Project 1: This project will develop a world-leading solution for providing continuous electrical power to wearable health technologies. It is focussed on space medicine applications, specifically for integration within existing sensor units that monitor astronauts’ health characteristics. Existing monitoring devices are battery-powered, with short battery life. This project partners with the European Space Agency and an Australian company to develop a power source, using thermoelectric energy harvesting, that will power wearable sensors for years – perhaps decades – without ever needing re-charging, replacement or maintenance. Ultimately, the technology will have applications for all international space agencies, within space tourism and in other important Australian commercial sectors, such as defence, sports, first-responders, etc. Project 2: Industry 4.0 (i.40) will transform Australian manufacturing over the coming decade and beyond, enabling improved productivity, efficiency, agility and reduced costs. Wire-free sensors and actuators will be an essential ingredient of i4.0. However, a significant future issue will be how to provide power to these wire-free nodes. Using batteries alone will place a significant replacement/re-charging burden on a factory, when thousands of portable sensors are installed. Extending time between charges, or removing recharging completely, using cost-effective energy harvesting is one solution. Utilising an abundant factory waste product (low-grade heat) as a ‘fuel’ source is a smart way to achieve this, since – in parallel – it improves the factory’s energy efficiency. This project will extensively investigate the feasibility of thermal energy harvesting within the Australian manufacturing sector as a means to augment battery power. The project will benefit from access to NSWs’ only National Industry 4.0 Testbed as a ‘sandpit’ on which prototypes can be demonstrated. About the Supervisor This project will be supervised by Dr Nick Bennett. Nick recently joined UTS as a Senior Lecturer, having worked in the field of thermoelectric energy harvesting for most of the past decade. Previous to UTS, Nick worked at Heriot-Watt University in the UK between 2013 and early 2019, where he built a group, which – in its prime – consisted of 7 PhD/Postdoctoral Researchers. There he led seven projects in all, with total value above $1 million AUD, sponsored by the EPSRC, the Royal Society, the Energy Technology Partnership, the Energy Academy, and the Oil and Gas Innovation Centre, as well as completing research contracts/consultancy for numerous industry partners, including the European Space Agency and Mitsubishi. Dr Bennett is a recognised expert in thermoelectric energy harvesting, having been an invited speaker at some of the world’s foremost conferences on thermoelectrics. He was the co-organiser of the UK’s 2018 annual thermoelectric meeting. Successful candidates will join Dr Bennett’s team as founder members with the expectation that they produce world-leading research in the field of thermoelectrics. If you have what it takes to meet this challenge, please get in touch! Enquiries Contact Dr Nick Bennett for informal enquiries or apply, remember to include a copy of the following: (1) A brief covering letter (2) Curriculum Vitae (3) a copy of your degree certificate and transcripts. Topology Optimisation of Micro-lattice Metacomposites with Additive Manufacturing Scholarship: This project includes funding for a living stipend scholarship at the rate of $29,092 per annum (tax-exempt). Contact: Dr Zhen Luo Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic applications only. The goal of this project is to establish a new computational design methodology to address current challenges facing creation of ultralight lattice composites with ultra-high-performance characteristics. The latest advances in topological optimization and additive manufacturing will be systematically unified towards an integrated generative system, to produce multiscale, multifunctional lattice composite structures based on various meta-material microarchitectures (e.g. origami, acoustic, and thermoelastic metamaterials). The potential PhD student is expected to have (1) a solid background in computational mechanics (e.g. FEM, and Isogeometric Analysis) and structural optimization (e.g. topology optimization); (2) a demonstrated track record and experience in cellular/lattice composites and mechanical metamaterials; and (3) a strong will to learn and engage additive manufacturing, testing and property characterisation of the optimized lattice specimens. Triple-bottom-line of Industry 4.0 Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Mickey Clemon Duration: 3 years (possible 6-month extension) School: School of Mechanical and Mechatronic Engineering Closing date: when filled Domestic candidates only. Industry 4.0 is the application of advanced sensing, data analytics, robotics, and optimization to manufacturing. However this concept is in early in its development and the long-term impacts are yet to be determined. This project assesses the impacts to society, the environment, and production efficiency of applying Industry 4.0 techniques to various enterprises and applications. Visual simultaneous localization and mapping in deformable environments Scholarship: This project includes funding for a living stipend valued at $37,094 per annum (tax-exempt). Contact: Associate Professor Shoudong Huang Duration: 3 years (possible 6 month extension) School: School of Mechanical and Mechatronic Engineering Centre: Centre for Autonomous Systems Closing date: when filled Domestic candidates only. This project aims to investigate the problem of building a three-dimensional map of a deformable environment in real-time using images and at the same time localising the camera within the map. This project expects to generate new knowledge in the area of simultaneous localisation and mapping in deformable environments using visual sensors. Expected outcomes include in-depth understanding of the fundamental sensing requirements for the problem to be solvable, the achievable accuracy, and efficient algorithms for achieving accurate three-dimensional reconstruction of deformable environments. The research outcomes from this project is expected to offer significant benefits to diverse areas such as minimally invasive robotic surgery. We are looking for students with good mathematical background and programming skills. Previous research experience in mobile robot navigation and/or computer vision is a plus. Professional Practice and Leadership Developing authentic assessments in humanitarian engineering education Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Scott Daniel Duration: 3 years (possible 6-month extension) School: School of Professional Practice and Leadership Closing date: when filled Domestic and International applications accepted. Humanitarian engineering is an emerging engineering field that is being incorporated into the engineering curriculum at the University of Technology Sydney by the rollout in coming years of a humanitarian engineering sub-major. This will build on and complement existing subjects such as Engineering Communication and others which focus on the development of skills in human-centred design, socio-technical thinking, sustainability, and other skills related to humanitarian engineering. However, such skills can be challenging to teach, learn, and assess. This project will involve developing and validating scenario-based assessments for one or more of these skills, and using these assessments to evaluate student skill development. Developing tools for teaching and assessment of Indigenous cultural competencies for engineers Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Scott Daniel Duration: 3 years (possible 6-month extension) School: School of Professional Practice and Leadership Closing date: when filled Domestic and International applications accepted. Aboriginal and Torres Strait Islander peoples are the first peoples of Australia. They are also the first scientists, technologists, engineers and mathematicians, and the first practitioners of environmental sustainability and respectful community engagement. All engineering graduates are expected to be historically and culturally informed about the diverse cultural history and knowledge systems of Aboriginal and Torres Strait Islanders and build and maintain respectful and trustful relationships. One strategy for teaching and assessing cultural competencies in engineering is to develop authentic work scenarios that pose some situational judgement test. Examples from other cultures can be found at https://geec.info/gec-index. This project will involve consulting experts and reviewing literature to develop some clear, realistic scenarios that engineers working with Indigenous partners could face, and identifying a range of possible responses to those scenarios. These response options will be identified by comparing how novices and experts respond to the scenarios in an open-ended format, to ensure that they are all both plausible and indicative of different levels of Indigenous cultural competency. Gender equity in humanitarian engineering education Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Scott Daniel Duration: 3 years (possible 6-month extension) School: School of Professional Practice and Leadership Closing date: when filled Domestic and International applications accepted. Recent preliminary research into humanitarian engineering education has indicated a higher level of diverse participation than what is represented in the general engineering student cohort. In particular, gender participation has been seen to be at or near parity. This research will explore the underlying perceptions and motivations for students engaging in humanitarian engineering activities to understand this diverse participation. Extending on existing research that focuses on university student participation, this project will explore high school students’ perceptions of humanitarian engineering as well as industry professionals. The insights from this research will provide recommendations and inform how engineering education approaches can be shifted to enable more diverse participation in the sector. Key skills in humanitarian engineering Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Scott Daniel Duration: 3 years (possible 6-month extension) School: School of Professional Practice and Leadership Closing date: when filled Domestic and International applications accepted. The landscape of humanitarian engineering education in universities is rapidly expanding, with the number of programs in humanitarian engineering and related fields roughly doubling in the last decade. Ideally, these programs should equip students with the skills to be effective in humanitarian engineering work. But what are the key skills used in humanitarian engineering practice? And what skills learned in humanitarian engineering practice can be subsequently applied in mainstream professional engineering practice? To answer these questions, this project will build on some preliminary research already underway, and use interviews with professional engineers who have undergone humanitarian engineering work, such as EWB Field Professionals, Returned Australian Volunteers for International Development who undertook an engineering role, or engineers who have been deployed from the RedR Humanitarian Roster. A phenomenography of humanitarian engineering Scholarship: UTS Scholarship Scheme –Submit your application before the application deadlines and you will be considered for the UTS competitive scholarship scheme. Contact: Dr Scott Daniel Duration: 3 years (possible 6-month extension) School: School of Professional Practice and Leadership Closing date: when filled Domestic and International applications accepted. Humanitarian engineering is an emerging engineering field that is becoming increasingly incorporated into university engineering curriculum around Australia and the world, with various institutions offering subjects, minors, and even majors in the area. However, there remain competing definitions and interpretations of humanitarian engineering, ranging from emergency disaster relief, to design under constraint, to a broad set of skills and approaches that can be incorporated in mainstream professional engineering practice. Phenomenography is a research methodology for understanding the different ways a phenomenon is conceptualised, and can be used to identify the critical features that distinguish these different conceptualisations. This project will build on some preliminary research already underway, and use interviews with humanitarian engineering practitioners and academics to identify the key dimensions of contemporary humanitarian engineering practice. Acknowledgement of Country UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands. 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