Doktorarbeit an der UNSW Sydney

The Macreadie group at the University of New South Wales are looking to recruit a talented and enthusiastic student to join our research team. We are an inorganic chemistry group and interested in pairing fundamental inorganic chemistry and supramolecular chemistry to drive sub-angstrom control over the pore environment in metal-organic frameworks (MOFs) for storage, separation and catalytic applications.

Our group is interested in understanding the host-guest chemistry of MOFs and how this influences the structural and behavioral properties of the MOF. This includes investigating the gas capture of the MOF for different guests, structural changes in response to temperature and pressure, and also the catalytic properties of new frameworks. Our group is interested in using 3D-linkers to form 3D-linker MOFs (3DL-MOFs) which generally offer more sites for host-guest interactions compared with MOFs formed from traditional linkers. This project has a strong collaborative component with multidisciplinary groups from Australia, New Zealand, the USA and the UK, in addition to in-depth studies at the Australian Synchrotron, which allows for a deeper understanding of the MOF material properties. This work will involve some or all of organic and inorganic synthesis, MOF preparation, crystallography and gas adsorption. Some recent publications include: https://pubs.acs.org/doi/abs/10.1021/jacs.2c13715 and https://onlinelibrary.wiley.com/doi/abs/10.1002/anie.201916159

Skills gained: Single crystal X-ray diffraction (SCXRD), powder X-ray diffraction (PXRD), organic and inorganic chemistry synthesis, gas and vapour adsorption analysis.

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

The Australian funds management industry is seeing a major shift from collective investment products such as unit trusts to more individually oriented separately managed accounts (SMAs). New financial advice provided by financial planners now directs one in every two dollars of client money into the burgeoning $200 billion managed accounts sector. Responding to the lack of standards across SMAs for naming identical portfolios, calculating and presenting fees, classifying and reporting asset allocations, and tracking the roles of service providers, this collaboration will leverage new AI technologies that have powerful reasoning capabilities over large amounts of unstructured data. The outcomes are AI-enabled tools that provide rich user interfaces with the ability to continually integrate newly developed data standards and facilitate consistent SMA information provision to retail clients and institutional investors such as superannuation funds.

Despite its growing popularity, the SMA market is still struggling with identical portfolios having different names across platforms, fee structures that are impossible to compare, asset allocations that are reported using completely different methodologies, and inconsistent attribution of fiduciary roles between consultants/investment managers and platform operators. These problems pose major risks to financial advisers who are not able to meaningfully compare SMA products when selecting investments and tracking performance on behalf of investors. Led by the major players in the financial advice sector, SMA providers have adopted an industry-initiated set of data standards, the Separately Managed Account Standards (SMARS). The proposed PhD project interrogates gaps in the nascent standards, develops protocols and AI-driven tools for their maintenance, and performs a series of empirical studies utilising the newly standardised SMA data to provide evidence-based validation of investment outcomes, including risk-adjusted and post-fee performance rankings and performance attribution.

Based on rigorous data analytics and econometric studies, 

Project (a) will identify systemic gaps in the inaugural version of SMARS and develop AI tools for ongoing maintenance and updating of the standards and data collection protocols. 

Project (b) will improve the accuracy and timeliness of fund classification using machine learning algorithms to track SMA portfolio holdings and quantify the incremental value of implemented techniques compared to the base case of maintaining the status quo. 

Project (c) will utilize the corpus of clean SMA data produced by the proposal with machine-learning methods to exploit SMA characteristics to investigate the interactions between SMA characteristics and future performance. In Project (d) consistent SMA performance rankings will be produced and publicised. The project will be supported by the Fintech AI Innovation Consortium (FAIC), a new initiative building on the strength of digital innovation technology and AI capabilities of both the Engineering and Business faculties.

$39,206 per annum (2026 rate) up to 3.5 years + 29K per annum top up scholarship for 3.5 years.

Opportunity to apply for NIPhD top-up and Industry Partner top-up. 

Candidate must secure a UNSW main stipend ($39,206 per annum (2026 rate) up to 3.5 years).

Work on a cutting-edge project with the Australian Research Council Laureate Fellowship team

Description
PhD researchers are sought to join the Australian Research Council Laureate Fellowship team 'Caves and their stalagmites: linking climate to groundwater recharge'. The project is funded from 2025 to 2030, and we are looking to recruit PhD researchers to the team in 2027. 

International candidates will have to apply for a Tuition Fee Scholarship.

The specific projects are:
PhD 1: Climate, recharge, and groundwater sustainability (collaborating with Gabriel Rau, University of Newcastle).
PhD 2: Climate, recharge, and groundwater policy (collaborating with Marilu Melo Zurita and Cameron Holley, UNSW). 

https://www.unsw.edu.au/research/hdr/our-projects/caves-and-their-stalagmites-linking-climate-to-groundwater-recharge 
 

Are you passionate about vision science and innovation in eye care?

This exciting Industry PhD project offers the opportunity to explore personalised approaches to myopia management, in collaboration with Carl Zeiss Pty Ltd, the Australian arm of the globally renowned ZEISS Group.

Project Overview
Myopia is a progressive and irreversible condition that develops during childhood. Orthokeratology is an established method for correcting myopia and slowing its progression. However, treatment outcomes vary widely, likely due to the one-size-fits-all approach to treatment.

This research project will investigate how orthokeratology lens parameters influence corneal shape and optical defocus, with the goal of identifying key factors that enable truly personalised treatment strategies.

Industry Collaboration
Carl Zeiss Pty Ltd brings world-leading expertise in optics and optoelectronics, with a strong footprint in medical technology, vision care, and precision engineering. As an industry PhD candidate, you will work closely with ZEISS professionals and UNSW academics, contributing to impactful research that bridges science and industry.

This project is part of the prestigious National Industry PhD program providing the successful candidate with access to the Campus Plus national network, including a cohort of other National Industry PhD participants. Through this network, they will benefit from tailored professional development opportunities, industry connections and a strong professional community. 

$39,206 per annum (2026 rate) + $15,000 per annum top-up from our Industry Partner + $7000 NIPhD top-up.

https://www.unsw.edu.au/research/hdr/our-projects/optimising-performance-of-orthokeratology 

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. 

More than 50% of cancer patients receive radiotherapy (RT) as part of their treatment. Accurate tumour positioning during RT is crucial for effective therapy. However, physiological and involuntary patient movements during dose delivery can lead to suboptimal targeting and unintended high doses to healthy tissues, compromising treatment efficacy and increasing toxicity risks. Over 98% of RT patients worldwide are treated with general-purpose linear accelerators (linacs), which lack real-time target position adaptation.

This project aims to develop and validate a Dynamic Couch system, a moveable patient couch that adjusts in real time during RT to compensate for motion, ensuring precise tumour positioning. This system will enable safer reductions in safety margins, lowering radiation exposure to critical structures and minimizing toxicity. By project completion, a prototype will be ready for clinical trials. 

The Dynamic Couch system will enhance RT precision for >98% of patients, improving tumour control and reducing treatment-related toxicity. 

This project is in collaboration with South Western Sydney Local Health District and is part of the prestigious National Industry PhD program providing the successful candidate with access to the Campus Plus national network, including a cohort of other National Industry PhD participants. Through this network, they will benefit from tailored professional development opportunities, industry connections and a strong professional community.

~$56,206 p.a. tax free. This includes: UNSW scholarship, industry and NIPhD top-ups.

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

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. 

Designing for appropriate public interior environments demands a comprehensive understanding of user experiences, particularly in where people inhabit the same space for extended periods, such as restaurants, cafes, libraries, and communal workspaces. In these settings, acoustic quality / acoustic performance is a critical component for user comfort. The way the sound interacts with the space becomes a defining parameter that shapes usability, behaviour, communication, and the overall spatial experience.

As everyday soundscapes grow increasingly complex, the relationship between design decisions and acoustic experience becomes more critical. A user centred approach to acoustic design therefore requires an integrated understanding of both the qualitative and quantitative aspects of the acoustics and the perceived reasons behind how people interpret and respond implement to them in the finished building.

We are seeking proposals for projects for either PhD or MPhil that investigate the acoustic performance of architectural spaces through the application of a mixed method approach.

Proposals may include (but are not limited to) studies that compare acoustic conditions in public interiors with patterns of behaviour, wellbeing, or social interaction.

The aim of the research is to demonstrate that acoustics and hence the resulting soundscape as fundamental design factors, to inform future design decisions and enhance the lived experience of users in shared environments.

$39,206 per annum (2026 rate), $5,000 per annum research allowance.

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.

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

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.