Hydrogen embrittlement (HE) continues to pose a significant, unresolved challenge within the industrial sector. When hydrogen-rich environments interact with steels, especially those of high strength, HE can lead to diminished toughness and premature failure, significantly curtailing the range of industrial applications for these materials. HE typically manifests as cleavage-like failures, often occurring along grain boundaries (GBs) in polycrystalline metals, such as iron. In this project, molecular dynamics simulations will be conducted to understand the behaviour of crack tips along GBs in the presence of hydrogen. Our objective is to enhance our comprehension of hydrogen-induced plastic deformation and failure mechanisms in metallic materials.

Primary Academic Supervising- Prof Cheng Lu
Email- chenglu@uow.edu.au
Project Duration- 10 weeks

Carbon Capture and Storage stands as a pivotal technology in the battle against greenhouse gas emissions. High-pressure pipelines represent an efficient means for transporting CO2 from industrial emitters to designated storage sites, often geological wells. Given the potentially hazardous asphyxiating nature of CO2, it poses safety risks to the nearby populations situated along these pipelines. Therefore, gaining a more comprehensive understanding of fracture propagation holds the potential for both enhanced safety measures and economic advantages. In this project a fluid structure interaction simulation will be conducted to analyse the fracture propagation process in CO2 pipeline using Abaqus.

Primary Academic Supervising- Prof Cheng Lu
Email- chenglu@uow.edu.au
Project Duration- 10 weeks

This undergraduate research aims to explore the intersection of machine and robot design with a focus on harnessing green energy through permanent magnets. The project will involve utilizing Finite Element Analysis (FEA) simulations to optimize the design of machines and robots that incorporate permanent magnets for energy generation and efficiency. By leveraging FEA, we aim to enhance the performance of these devices, ultimately contributing to sustainable energy solutions. This research will not only offer valuable insights into machine and robot design but also promote the development of eco-friendly technologies for a greener future.

Primary Academic Supervising- Dr Chin-Hsing Kuo
Email- chkuo@uow.edu.au
Project Duration- 12 weeks

This project aims to develop deep learning algorithms for generating coloured and textured camouflage patterns to mimic or blend with a specific environment. These tools have important applications in wildlife conversation, recreation and sports, fashion and design, and many other areas. The project tasks will include image acquisition, algorithm development, system implementation, and evaluation. The candidates are expected to have a strong background in deep learning and proficiency in AI/ML libraries (e.g., Pytorch and/or Tensorflow).

Primary Academic Supervising- Dr Thanh Le Hoang
Email- tlhoang@uow.edu.au
Project Duration- 10 weeks

This project will involve construction and set up of a robot that has been designed to simulate walking gait on an amputated leg. The student will  be responsible for collaborating with the workshop to construct the robot and then implementing relevent programming and sensor calibration to enable simulations can be run and data can be collected. This project will suit a student with biomedical and/or mechatronics experience.

Primary Academic Supervising- Dr Lucy Armitage
Email- alucy@uow.edu.au
Project Duration- 10 weeks

Laboratory testing of brittle materials to investigate fracturing modes and stress tensors for Rockburst.

Primary Academic Supervising- Dr Justine Calleja
Email- jcalleja@uow.edu.au
Project Duration- 10 weeks

Signs of dementia are usually vague making early diagnosis very challenging. While there is emerging evidence showing that gait analysis has the potential to contribute to diagnosis/prognosis of dementia, knowledge of how gait changes are exactly associated with dementia has been limited. Meanwhile, analyzing electrical activities of the brain during walking by recording electroencephalography (EEG) can give additional clues. However, further efforts are required to pick up useful signals from EEG recording which is usually
contaminated with artifacts during physical movements. The main aim of this research is to conduct both movement and brain activity analysis together on people with dementia and identify clues from vast amount of data and noise signals making them helpful in predicting/ monitoring progress of dementia.

Primary Academic Supervising- Dr Wilson Lee
Email- ccwlee@uow.edu.au
Project Duration- 12 weeks

This project aims to develop a self-locking electrochemical-enabled Liquid Metal Actuator (SELMA). The SELMA is composed of two Galium droplets equipped with copper electrode through wetting mechanism, a temperature control system, and an actuation head. The steady actuation will be achieved by repeatedly reversing the electric field. To lock the position of actuation head, Galium droplet transfers into solid through the temperature control system.

Primary Academic Supervising- Prof Weihua Li
Email- weihuali@uow.edu.au
Project Duration- 10 weeks

This is an industry co-funded, co-supervised, and led project. The scholar will work with a dataset, conducting exploratory data analysis and applying statistical methods to extract meaningful insights. The student will validate any models built and statistical conclusions reached. These insights will then be conveyed in the form of a blog post, simplifying the language so that any non-technical individual could understand but without skewing the interpretation of the insights. The student will have regular meetings with supervisors to facilitate progress updates. Upon project completion, pending manager approval, the blog post will be posted on EdgeRed's website, enhancing industry exposure.

Primary Academic Supervising- A/Prof Xiaoping Lu
Email- xplu@uow.edu.au
Project Duration- 10 weeks

Using high resolution photographs and photogrammetry software, Capturing Reality, we will create  3D interactive digital twins of buildings such as Desert Rose House.  These will be integrated with the Unreal games engine by Epic Games.

Primary Academic Supervising-  Prof Timothy McCarthy
Email- timmc@uow.edu.au
Project Duration- 10 weeks

Biofuels such as wood waste and agricultural waste are used as fuel in renewable incineration energy systems. The ash has the potential to be incorporated as a supplementary cementitious material. This project will examine the chemical and physical properties of biofuel ash from an industrial furnace to assess its potential  as an SCM.

Primary Academic Supervising- A/Prof Neaz Sheikh
Email- msheikh@uow.edu.au
Project Duration- 10 weeks

Antibiotic resistance genes (ARGs) in treated wastewater effluent is a significant concern as it can spread residual ARGs from waste to the environment. Sand filters are used in many wastewater treatment plants after the secondary treatment to enhance the effluent quality. They can serve as an important barrier before the release of ARGs in wastewater effluent. This project will investigate the performance of sand filters in removing different ARGs by studying three local Wastewater Treatment Plants. Wastewater samples and filter media samples will be obtained to understand the removal mechanisms and impacting factors.

Primary Academic Supervising- A/Prof Guangming Jiang
Email- gjiang@uow.edu.au
Project Duration- 10 weeks

During this project, the student will be tasked with characterising a novel diode system for in-vivo source tracking in HDR brachytherapy. To achieve this the student will work with the detector system at St George Cancer Care Centre and characterise the response of the detector under different irradiation conditions using an Ir-192 source. The data collected using these measurements will be used to develop an in-vivo source tracking algorithm specific to this detector design, eventually utilising the detector system coupled to an ultrasound probe for a clinical trial of HDR prostate brachytherapy in-vivo source tracking at St George Cancer Care Centre.

Primary Academic Supervising- Dr Joel Poder
Email- jpoder@uow.edu.au
Project Duration- 10 weeks

The student will be tasked with determining the number of targets requiring fluence measurements for multiple-target single-isocentre stereotactic radiosurgery by simulating potential errors in treatment planning and delivery using pre-existing code. The outcome of the project will be recommendations on which targets are most susceptible to these errors, optimizing the quality assurance process for these treatment plans.

Primary Academic Supervising- Dr Joel Poder
Email- jpoder@uow.edu.au
Project Duration- 10 weeks

In this project, a newly developed silicon microdosimeter with 3D sensitive volumes is proposed to overcome the shortcomings of the conventional Tissue Equivalent Proportional Counter. The electrical and charge collection characteristics of a new 3D SV microdosimeter with 10 µm thick in response to different types of ions will be investigated using the ANSTO heavy ion microprobe. 
The SOI microdosimeter is used to measure the lineal energy deposition of 230MeV/u He ion and then derive relative biological effectiveness (RBE) and compare with proton therapy. Fragmentation contribution will also be studied.
The project will involve electrical and spectral characterisation of the silicon microdosimeters and analyse data obtained in heavy ion beam in Heavy Ion Medical accelerator in Chiba (HIMAC), Japan. The project might involve Geant4 simulation of the experimental setup and compare with the experimental results.

Primary Academic Supervising- Dr Linh Tran
Email- tltran@uow.edu.au
Project Duration- 12 weeks

Load Modelling is off key importance to power system operators. The current static load models used by the Australian Energy Market Operator (AEMO) is unable to accurately model the complex network behaviour due to the significant change in the end-user composition of load and increase in the number of Electric Vehicles (EVs) in the network.  In close collaboration with AEMO, the objective of this project is to conduct extensive experimental testing on contemporary EV loads under various voltage, frequency, and phase disturbances. The insights derived from these comprehensive tests will serve as the cornerstone for developing dynamic load models that can effectively simulate the behaviour of EV loads within the evolving landscape of future power systems.

Primary Academic Supervising- Dr Obaidur Rahman
Email- orahman@uow.edu.au
Project Duration- 12 weeks

Gaussian process emulators are random functions that can be used to interpolate between numerical solutions of mathematical models (e.g. Navier-Stokes partial differential equations). This can reduce the computational cost when the model in question is expensive to solve. For example, a computational fluid dynamics model that takes 6 weeks and 1 million CPU core hours to solve numerically. This project will involve a combination of numerical analysis and practical application of statistical methods. The student will first investigate the theoretical properties of Gaussian processes. They will then write Python code to fit a Gaussian process emulator for a CFD model.

Primary Academic Supervising - Dr Matt Moores
Email- mmoores@uow.edu.au
Project Duration- 8 weeks

This project aims to develop deep learning and GPS mapping tools for satellite and drone imaging applications. These tools can be used for environment monitoring, precision agriculture, space surveillance, infrastructure management and many other areas. The project tasks will include image acquisition, data annotation, algorithm development, system implementation and evaluation. This project seeks a student (in computer engineering, computer science, or a related major) with experience in Python/MATLAB programming and a strong interest in a postgraduate research study on machine learning and AI.

Primary Academic Supervising- Prof Son Lam Phung
Email- phung@uow.edu.au
Project Duration- 10 weeks

This project involves working with the Australian Power Quality Research Centre in conjunction with Shoalhaven Water to deploy energy storage technologies designed to improve the resilience of Shoalhaven Water pumping sites. The successful student will assist with modelling and analysis of the energy storage systems including investigation of the potential for operation as a virtual power plant. The student can expect to be undertaking work in both the Shoalhaven region as well as at the Sustainable Buildings Research Centre at the University of Wollongong.

Primary Academic Supervising- A/Prof Duane Robinson
Email- duane@uow.edu.au
Project Duration- 12 weeks

This project involves working with the Australian Power Research Centre in conjunction with Shoalhaven Water to deploy energy storage technologies designed to improve the resilience of Shoalhaven Water pumping sites. The successful student will assist with commissioning of the systems and ongoing performance assessment through deployment of field measurements systems and analysis of collected data. The student can expect to be undertaking work in both the Shoalhaven region as well as at the Sustainable Buildings Research Centre at the University in Wollongong.

Primary Academic Supervising- A/Prof Duane Robinson
Email- duane@uow.edu.au
Project Duration- 12 weeks

This project involves development and deployment of software and hardware to visualise the energy generation, demand and battery storage system status at the SBRC. The student will be undertaking work at the SBRC on the UOW innovation campus.

Primary Academic Supervising- A/Prof Duane Robinson
Email- duane@uow.edu.au
Project Duration- 12 weeks

A particular challenge in using silicon-based microdosimeters is the poor signal-to-noise ratio for low-LET doses. In the case of the SOI-microdosimeters devices produced by the CMRP, the low-LET threshold for detection is on the order of 0.4-0.8keV/μm. The CMRP proposed solution to overcome noise limitations in order to measure microdosimetric quantities from low LET radiation using a silicon device with an intrinsic gain. The implementation of LGADs for particle detection is challenging and suffer a gain suppression. This phenomenon is a result of the induced plasma column with a large carrier density around the incident particle track as it traverses the detector. Therefore, the response of LGAD to different types of ions of different energies are of great interest. The electrical and charge collection characteristics of irradiated LGAD detectors and response to protons will be investigated using the ANSTO heavy-ion microprobe. Effect of radiation damage will be studied.

Primary Academic Supervising- Prof Anatoly Rozenfeld
Email- anatoly@uow.edu.au
Project Duration- 12 weeks

This project aims to develop a new teleoperated robotic hand that can easily adapt to different industrial tasks by acquiring new skills from human workers to improve the flexibility and productivity of manufacturing processes. With the real-haptic sensation-based human-to-robot skill transfer technique and the intrinsically safe actuation technology, the proposed teleoperated robotic hand can i) safely work alongside humans in open factory environments, ii) perform more delicate tasks than existing robotic systems, and iii) be rapidly reconfigured for different tasks by human workers who will not have to be trained in robotics and programming.

Primary Academic Supervising- Dr Emre Sariyildiz
Email- emre@uow.edu.au
Project Duration- 10 weeks

Phantoms approximating human body parts are used are medical trainers but tend to be prohibitively expensive, or do not provide effective feedback to the trainee and the educator. In this project, we will develop instrumented phantoms using innovative 3D printing and inexpensive sensor technology to make them more accessible. This topic will be carried out in collaboration with the Illawarra Health Education Centre at Wollongong Hospital, part of the Illawarra Shoalhaven Local Health District. Students should have strong aptitude for experimental work, signal processing, 3D printing and good programming experience. Knowledge of physiology would be beneficial but not critical.

Primary Academic Supervising- Dr Manish Sreenivasa
Email- manishs@uow.edu.au
Project Duration- 10 weeks

This project will investigate the influence of ketosis on the treatment outcomes of certain emerging brain cancer therapies (namely PAC-1 and PAC-1 combined with TMZ, radiotherapy). Specifically, the experiments will unravel the link between certain processes (senescence, apoptosis) with the relevant therapies. Additionally, the project will translate these treatments to a three-dimensional cell model (spheroids) in attempt to better mimic the physiological conditions of the tumour.

Primary Academic Supervising- Dr Moeava Tehei
Email- moeava@uow.edu.au
Project Duration- 8 weeks

Integrating the heat pump technology, geothermal warming of mine waters can be transformed into renewable energy technology. This research aims to assess the feasibility of utilizing mine water geothermal technology for space heating applications. The primary objective is to evaluate potential options for harnessing geothermal heat from underground mines and develop a methodology for identifying prospective locations. The project expects to access GIS data, geothermal energy maps, geological data and mine site data to identify potential sites for mine water geothermal technology in the Australian context.

Primary Academic Supervising- Prof Pabasara Wanniarachchige
Email- pabasara@uow.edu.au
Project Duration- 10 weeks

Assist research staff in undertaking experiments into the thermal performance of various wall systems.  Candidates with strengths and interest in heat/mass transfer and fluid dynamics are preferred.
Opportunities to design and build 'Internet of things' (IoT) equipment to measure air velocities near the test specimen, and/or to develop python or Matlab scripts to analyse data and model aspects of the physical processes involved, will also be possible.

Candidates with strength and interest in heat/mass transfer and fluid dynamics would be most suitable.

Primary Academic Supervising - Dr Alan Green
Email- alang@uow.edu.au
Project Duration- 10 weeks

This project is part of an interdisciplinary effort aimed at enhancing the occupational health and safety of construction workers by significantly advancing current wearable sensor-based ergonomic monitoring methods. The primary goal of this project is to develop deep learning-based algorithms capable of correlating data from a detailed laboratory movement recording system with that from a more portable and wearable open-source device.

Ideally, the student involved in this project should have a strong aptitude for Python or a similar programming language that supports the development of deep learning algorithms. This is a desktop study that involves using Python's deep learning libraries to correlate data recorded from a pilot study.

Primary Academic Supervising- Dr Aziz Ahmed
Email- aziza@uow.edu.au
Project Duration- 8 weeks

Bamboo, a rapidly growing and self-regenerating grass, stands as a clear example of sustainable construction material. However, the utilization of Engineered bamboo in Australian construction remains relatively uncharted. This desktop study aims to address this gap by conducting a comprehensive Life Cycle Assessment (LCA) that compares Engineered bamboo with traditional timber-based construction materials. Leveraging Open LCA software and the eco-invent database, the study delves into the environmental impact and sustainability aspects of these materials. Ultimately, it seeks to shed light on the ecological benefits and feasibility of incorporating Engineered bamboo into the construction industry in Australia.

Primary Academic Supervising- Dr Aziz Ahmed
Email- aziza@uow.edu.au
Project Duration- 8 weeks

Absence of resistance, revolution in energy handling and generation, new superconducting electronics, single photon and single proton detection for space and medicine, quantum supremacy, quantum vortices, high energy particles probing superconducting quantum states, magneto-optical imaging, these are just a few key words highlighting what is explored within this project tailored individually for every interested student with the help of the state of the art equipment and theory.

Primary Academic Supervising- Prof Alexey Pan
Email- pan@uow.edu.au
Project Duration- 10 weeks

Thin film technologies, surface and interfacial sciences, nano-technologies, hybrid structures (magnetism, superconductivity, semiconductors), novel phenomena at interfaces explored by neutrons, high density magnetic storage systems, spintronics (spin-electronics) and novel devices, these are just a few key words highlighting what is explored within this project tailored individually for every interested student with the help of the state of the art ultra high vacuum and low temperature facilities and theory.

Primary Academic Supervising- Prof Alexey Pan
Email- pan@uow.edu.au
Project Duration- 10 weeks

The Internet of Things (IoT) has transformed the digital world and is indispensable in various sectors such as healthcare and agriculture. However, the increasing volume of data generated by IoT devices poses significant security concerns for intrusion detection systems (IDS) that require efficient strategies to process and analyse large-scale data to ensure the security of IoT systems. Current research solutions have explored software-defined networking (SDN) and machine learning (ML) techniques for protecting IoT systems. However, a critical challenge lies in the limited availability of IDS datasets tailored for ML-based SD-IoT models. This project aims to address this challenge.

Primary Academic Supervising-  Dr Chau Nguyen
Email- chaun@uow.edu.au
Project Duration- 10 weeks

Lithium-based peritectic compounds offer exciting potential for thermal battery applications in the solar energy storage industry due to their ability to store and release high thermal energy during solid/liquid transitions. In this project, students will collaborate with researchers to investigate phase transition behaviors during temperature cycling and analyze the thermal responses of several candidate materials. Experimental methods such as high-temperature microscopy, thermal analysis (DTA/DSC), and X-ray diffraction will be employed to test materials. Students will actively contribute to laboratory work and gain valuable insights and techniques for developing new materials. Applicants with knowledge of thermodynamic phase equilibrium and chemistry are welcome to apply.

Primary Academic Supervising-  Dr Suk Chun Moon
Email- scmoon@uow.edu.au
Project Duration- 8 weeks

In Machine Learning and Statistics, gradient descent is widely used to learn a probabilistic model for data, and natural gradient descent is largely regarded as the ``gold-standard’’ [1,2]. This project is a deep-dive into the theory and implementation of natural gradient descent, to understand its convergence properties, and explore its efficient implementation for large models and massive data sets.
This project covers contemporary Machine Learning methods, and potentially pursued further as a post-graduate research topic.
[1] Amari, S.-I. “Natural gradient works efficiently in learning.” Neural Computation, 10(2): 251–276, 1998.
[2] Martens, J. “New insights and perspectives on the natural gradient method,” JMLR, 21: 1-76, 2020. https://arxiv.org/abs/1412.1193

Primary Academic Supervising-  Prof Sumeetpal Singh
Email- sumeetpals@uow.edu.au
Project Duration- 10 weeks

We invite applications for an exciting summer scholarship project that leverages artificial intelligence (AI) for aged care service improvement. The successful candidate will join a multidisciplinary project team committed to developing an industry-grade AI-powered application designed to revolutionise malnutrition management in aged care. You will contribute to the integration of machine learning techniques into healthcare solutions. Learning Outcomes: Access to state-of-the-art generative artificial intelligence technologies and super computing resources. Gain hands-on experience in Cloud-based service development. Collaborate with leading researchers and professionals in technology, health, and aged care. Potential for future employment or research collaboration.

Primary Academic Supervising-  Prof Ping Yu
Email- ping@uow.edu.au
Project Duration- 12 weeks

This project involves undertaking a review of the Sustainable Buildings Research Centre (SBRC) FlexGrid laboratory infrastructure. Key tasks will include cataloguing equipment, re-commissioning of devices and compilation of documentation. The project will also involve undertaking a preliminary analysis of the demand response capability of equipment at the SBRC. The student will be undertaking work at the SBRC on the UOW innovation campus.

Primary Academic Supervising-  Dr Craig Mclachlan
Email- cmclauch@uow.edu.au
Project Duration- 12 weeks

Dynamic wetting and interfacial tension of liquid oxides on ceramics as measured using a high temperature sessile drop apparatus. These data are extremely important for use in understanding and characterising metal processing.  As well as getting experience in the use of high temperature equipment the student will get experience of utilising the University scanning electron microscopes.

Primary Academic Supervising-  Dr Ray Longbottom
Email- rayl@uow.edu.au
Project Duration- 12 weeks

The aim of the project is to build a satellite ground station to communicate with CubeSats.

Primary Academic Supervising-  A/Prof Raad Raad
Email- raad@uow.edu.au
Project Duration- 8 weeks

Hydrogen energy has been introduced as a promising clean source of energy. It has been foreseen that there will be wide applications in the near future. The storage of hydrogen is the most important stage from production, transportation to utilisation. This research will conduct a review and analysis of promising technologies applied to hydrogen storage. It depends on the specific topic selected, some simulation models will be developed. The outcome will be the comparison analysis results of the promising technologies not only from technological perspective but also from social-economic impact. The future research directions and potential applications will be highlighted.

Primary Academic Supervising-  Dr Tieling Zhang
Email- tieling@uow.edu.au
Project Duration- 12 weeks

The interest in implementation of collaborative robotics (cobots) are steadily increasing within Australian industry. Systems where cobots have been designed to work with humans are becoming more prevalent. Although there are standards providing guidance on the safety of machinery and cobots, issues related to potential harm arising from the interactions between workers and cobots in a shared work environment are not fully understood. This research will identify risks and harms to workers working with cobots through literature review study; develop risk assessment and simulation models for specified environments; work out principles for safe cobots; and indicate the future research directions.

Primary Academic Supervising-  Dr Tieling Zhang
Email- tieling@uow.edu.au
Project Duration- 10 weeks

There is a need to reduce the oil based products as they have significant environmental impacts. The project involves development and testing of a number of bio-based lubricants such as safflower oil for cutting fluids, transformer fluid or fluid for metal rolling. The lubricants need to overcome many issues such as oxidation, high pour point, etc..to be more acceptable in industry. The isssues can be overcome with additives but with additional costs. The acceptance of the bio-lubricants needs to be balanced between the performance and cost which will be benchmarked against existing oil-based lubricants.
The project involves
(i) a literature review on the state of the art of the bio lubricants for industrial applications
(ii) formulate the test lubricants with additives
(iii) friction and wear tests on ball on disc tribometer to determine friction and wear of the balls and disc at different temperatures up to 500oC
(iv) Characterise the nature of the ball and disc surfaces to understand how the bio-lubricant behaves in the contacts.

Primary Academic Supervising-  Prof Kiet Tieu
Email- ktieu@uow.edu.au

Co-Supervisor - Dr Bach Tran
Email- bach@uow.edu.au  
Project Duration- 12 weeks

The construction industry is responsible for 40% of the total waste generation in Australia, however C&D waste data is highly aggregated, with very little data available around the source of waste, specific materials or how avoidable/recoverable the waste is. There is currently no established standard for measuring and benchmarking construction waste. This project will involve investigating measurement techniques available as well as the challenges involved in construction waste data collection at a local or regional scale. Through liaising with local waste collection points, it aims to identify best practice approaches to measure waste generation on a larger scale.

Primary Academic Supervising-  Dr Leela Kempton
Email- leelak@uow.edu.au
Project Duration- 10 weeks

This project will look at applying a carbide grid to a welding process for hard facing applications. This project will involve establishing an optimised welding procedure with experimental setup of grit application.

Primary Academic Supervising- Dr Philip Commins 
Email- pcommins@uow.edu.au
Project Duration- 10 weeks 

This project will look at applying a carbide grid to a welding process for hard facing applications. This project will involve establishing an optimised welding procedure with experimental setup of grit application. 

Primary Academic Supervising- Dr Philip Commins
Email- pcommins@uow.edu.au
Project Duration- 10 weeks

This project will involve evaluating the response of electric vehicle charges to variations in the supply voltage magnitude. The project will be experimental and will involve testing a number of EVs and chargers.

Primary Academic Supervising- Dr Sean Elphick
Email- elpho@uow.edu.au 
Project Duration- 11 weeks