Promotion in Ingenieurswissenschaften, Informationstechnologie und Computer Sciences

This PhD is an exciting opportunity for a highly motivated candidate who wants to see their research translated into clinical practice and directly benefit patients. The project aims to develop personalised models of patients' pre- and post-Percutaneous Coronary Intervention (PCI) with stents.

During the course of this PhD, the successful candidate will attain the required ethical approval and collect patient-specific imaging data before running a range of computational and experimental tests.

The right candidate will work closely with a multi-disciplinary team across medicine, computer sciences and mechanical engineering. Relevant previous research experience is desired. The right candidate must be an experienced ANSYS fluid dynamic user or similar and have a good fluid dynamic understanding in the biomedical engineering context. 

Strong problem-solving skills, motivation and good communication skills are required. An interest in and willingness to learn about cardiovascular disease is critical. Previous experience in publishing is highly desirable.

You will be part of an international, dynamic, and thriving team based in Sydney, Australia, which values teamwork, inclusivity, and excellence. Weekly group and individual meetings will allow you to excel in your work. For more details, please see www.svmgroup.org. 

Female applicants are highly encouraged. 

Heart valves often become weak with old age, previously a common cause of death. Open heart surgery has been too invasive in the past. However, a new minimally invasive procedure (called TAVI) has now made this intervention safer and more accessible, helping many affected patients worldwide live longer, better quality lives.

Still, the success of the surgery largely depends on the quality of the medical imaging during the implant of the new value, which is 2D, greyscale and often has a poor spatial and temporal resolution. Immersive technologies such as AR and VR have rapidly emerged in recent years, but their translation into the surgery room remains fictional.

This PhD will explore how AR and VR technology can be integrated as tools to assist live surgical TAVI procedures. The ideal candidate has a strong programming background and experience with immersive technologies. Strong problem-solving skills, motivation and good communication, and a passion for health technologies are required.

This interdisciplinary PhD is an excellent opportunity for a postgraduate student to pursue world-leading and novel research of significant translational impact, offering various career paths and stimulating intellectual challenges. 

The project will bring together leading experts from creative technologies, engineering and medicine as a supervisory and advisory team as part of an international, dynamic, and thriving team based in Sydney, Australia. We value collaboration, inclusivity, and excellence. Weekly group and individual meetings will allow you to excel in your work. For more details, please see www.svmgroup.org.

 Female applicants are highly encouraged. 

This PhD is an exciting opportunity for a highly motivated candidate with academic ambitions. The project aims to develop a new suit of biofluids solver as a significant advance for medical diagnostics and device development.

During this PhD the successful candidate will develop physics-informed neural networks to accurately predict fluid dynamics in large generalised vascular networks such as the coronary artery tree or the Circle of Willis.

The right candidate will work closely with a multi-disciplinary team across medicine, computer sciences and mechanical engineering. Relevant previous research experience is desired. The right candidate must be an experienced Python user and should have worked with neural networks before. A good fluid dynamic understanding, especially for biological systems, and a strong mathematical understanding are preferable. 

The continuous increase in energy conversion efficiency and decrease in cost have made solar power the cheapest form of electricity in most countries. As a result, silicon-based solar cell technologies are dominating the global photovoltaic (PV) market. However, as the efficiency of silicon single junction solar cells approaches its theoretical limit, the PV industry and research community are turning their attention to next-generation technologies like tandem solar cells. Tandem solar cells use multiple layers of light-absorbing materials with different bandgaps to better utilise the solar spectrum, making them more efficient than single-junction cells. While tandem solar cells are an exciting new technology, they still require intensive research to become commercially viable.

Characterisation plays a vital role in the development of solar cells. Note that the world record for silicon solar cell efficiency that had been held by UNSW for many decades was strongly supported by the availability of state-of-the-art characterisation tools. In this project, we are seeking a motivated PhD candidate to develop advanced characterisation techniques for tandem solar cells to bring transformative change to the PV industry. More specifically, you will develop:

Advanced in-depth characterisation techniques to better understand the material properties and device physics of tandem solar cells, assisting the optimisation of tandem solar cells.
High throughput quality-inspection techniques to facilitate the mass production of tandem solar cells.
You will explore multiple advanced characterisation techniques including Kelvin probe, magnetic field imaging, hyperspectral imaging, and many more. You will also innovatively adapt several existing characterisation techniques for single junction solar cells to tandem solar cells, such as luminescence imaging, time-resolved photoluminescence, etc. Through a collaborative environment, you will get access to state-of-the-art laboratories, high efficiency tandem solar cells, as well as industrial large area devices. Apart from hands-on experience during the developing of novel characterisation systems, you will also gain knowledge and skills in simulation and loss analysis of tandem solar cells. 

$37,684 per annum (2024 rate, indexed) for 3.5 years. International candidates will receive a tuition fee scholarship.

Commercial maturity of Power-to-X (P2X) technologies to utilise renewable energy resources for electrochemical conversion of abundant molecules like water, CO2, and N2, into green renewable energy-carriers, fuels and chemical feedstocks have opened new avenues for deep-routed decarbonisation. A transition that is well underway, with 25 of the world’s largest and leading economies introducing policies and incentives to kick start the P2X economies, leading to large scale up of electrolyser manufacturing, renewable energy deployment for P2X and a commitment of investment of ~240 billion USD.

Yet only 4 - 10% of these investment commitments have reached a final investment decision (FID). The critical bottlenecks are the current high cost of electrolysis technology, renewable electricity, and low capital efficiency of the projects due to intermittent and variable operation of solar/wind energy sources which results in high production costs making them unviable against their fossil fuel counterparts. However, there is expectation that the cost of P2X will decrease with ongoing cost reduction in electrolyser and renewable energy production, achievement of economies of scale and optimisation of project designs. Therefore, in the meantime while the cost remain high and relatively incompetent for large scale offtake, there is a need to find niche utilisation opportunities to enable scale up of technology.

This PhD project will focus on the technoeconomic analysis (TEA) of various Power-to-X conversion pathways, with an emphasis on modelling end-use scenarios (such as chemical manufacturing, green steel production, etc.). In order to inform and determine the commercial feasibility of these pathways, the student will use and build on existing TEA models and frameworks developed at GlobH2E. Hence a background in technoeconomic analysis, project design, simulation tools like Aspen/DWSIM, Excel VBA Programming, HOMER, excel and python coding would be beneficial, but not essential. 

$37,684 per annum (2024 rate, indexed) for 3.5 years. International candidates will receive a tuition fee scholarship.

The emergence of AI teaching assistants marks a new era in education, where non-human entities are integrated as tutors, aides, consultants, or even "machine instructors." 

This project aims at exploring the applications of AI in education, which may involve the design, implementation and evaluation of AI-powered teaching tools. 
Faculty of Engineering 

This project aims to understand how to build AI systems that humans can trust. It does so by studying how to make such systems fair, explainable, auditable, preserving of privacy and verifiable.

Outputs will include tools to build trustworthy AI systems, as well as policy recommendations to complement the technical tools. This should provide significant economic and societal benefits as decisions in both the public and private sector are increasingly being handed over to computers.

$37,684 per annum (2024 rate, indexed) for 3.5 years. International candidates will receive a tuition fee scholarship.

$37,684 per annum (2024 rate, indexed) for 3.5 years. International candidates will receive a tuition fee scholarship.

$37,684 per annum (2024 rate, indexed) for 3.5 years. International candidates will receive a tuition fee scholarship.

This project aims to pioneer innovations in green civil engineering by developing first-of-its-kind porous structures for Australian sustainable environment. It establishes novel graded porous geometries in cementitious structures for superior stiffness and thermal insulation. The lightweight yet robust structures with minimal cement usage are crucial to mitigating carbon footprints in civil construction and building operation with huge emissions. The project expects to develop new knowledge and advanced simulations in porous composites. This will help Australia growing green civil industries with significant economic benefits and achieving the Net Zero Plan via saving building operation energy and reducing construction emissions and waste.

The candidate will work closely with industrial partners and academics from different Universities/Schools. The success of this project will bring the candidate
1) exceptional research achievements; 
2) wide industrial and academic connections; 
3) a great career path as a composite engineer/researcher in civil and mechanical engineering.

$38,438 per annum (2025 rate). Other supports will also be provided, including opportunities to assist teaching and to attend international conferences.

AI-Enhanced Battery Management and Safety for Battery Energy Storage Systems. 
This project will develop advanced battery management and safety technologies for next-generation energy storage systems, with a focus on improving performance, reliability, and lifespan. Working with industry partners, it will integrate artificial intelligence, physics-based modelling, and real-time sensing to accurately assess battery health, predict failures, and optimise operation under diverse conditions.

The research addresses critical challenges in deploying large-scale and second-life batteries for renewable energy integration, electric mobility, and grid stability. By detecting faults early and enhancing control strategies, the project aims to reduce downtime, improve safety, and lower lifecycle costs.
Outcomes include validated algorithms, prototype systems, and guidelines for industry adoption. This work will accelerate Australia's transition to a cleaner, more resilient energy system, strengthen local manufacturing and recycling capabilities, and create commercial opportunities in global energy storage markets. 

$39,206 per annum (2026 rate) up to 3.5 years. $10,000 industry top-up.

For more information about this project please contact A/Prof Huadong Mo. 
https://www.unsw.edu.au/research/hdr/our-projects/ai-enhanced-battery-management-and-safety-for-battery-energy-storage-systems.

This project will develop a framework to optimise the schedule and operation of electrified transportation fleets. 

It will predict batteries performance, detect anomalies in real time, manage schedule uncertainties, adapt to battery health, charger availability and unexpected delays.

Expected outcomes include improved reliability and efficiency, extended battery life and reduced operational costs. 

Are you an engineer, software developer, or perhaps the AI wizard looking to make a big impact in environmental sciences and drug discovery? We have an exciting PhD project that is perfect for you!

We are seeking talented and innovative PhD candidates to develop algorithms that enable video-based real-time tracking of aquatic model organisms in complex environments on a large scale. This interdisciplinary project will pioneer new algorithms and innovative methods to provide the world's first inherently scalable behavioral bioanalysis, unlocking cognitive research in aquatic eco-neurotoxicology and neuroactive drug discovery. Additionally, the outcomes of the project will enable novel scientific discoveries in neurobiology research on aquatic animals.

The lack of automated and high-throughput cognitive tests in aquatic model organisms is a major deficiency, but with your help, we can change that. This project will provide the first-ever unbiased and automated analytical systems for cognitive eco- & neurotoxicology, allowing us to assess how diverse neuroactive pollutants and/or drugs affect higher neurological functions of aquatic animals.

Don't miss this opportunity to be at the forefront of ground-breaking research at the Neurotox Lab at RMIT University. As one of Australia's leading experts in eco-neurotoxicology, we are exploring how pollutants impact animal behavior and neurodevelopment, as well as elucidating the neurobiological foundations underlying changes in animal behavior.

By joining this PhD project, you will have the opportunity to work in an exciting and rapidly growing interdisciplinary field. Apply now and join us in making a difference in the world.

The applicants can apply for RMIT Higher Degree by Research International Scholarship upon being granted an offer of admission to an RMIT research training program. The deadline for the next International Scholarship round will be 15th September 2023.