Scholarship opportunities

Hydrogels with mechanical properties for 3D in vitro cell models

This Project combines different polymer chemistries to develop hydrogels that can be made stiffer or softer on-demand, replicating physiological processes. The expected outcome is the creation of hydrogels for 3D cell culture that better mimic native tissues in different stages of their development and disease. The potential benefit is improved in vitro/non-animal models with lower attrition rates and cost in drug discovery and development of advanced therapies.

Influencing factors of feed intake and digestion in prawns

This Project will investigate poorly understood mechanisms regulating feed consumption in prawns through a multi-disciplinary approach studying feeding behaviour, digestive physiology, nutritional needs and metabolism regulation. The expected outcomes are to better understand dietary factors and physiological mechanisms promoting feed consumption and return of appetite in juvenile prawns. This may lead to the application of new feed and feeding strategies to enhance aquaculture performance and sustainability.  

Prediction of molecular interactions with RNA using AI

This Project will develop deep-learning models to predict interactions of ribonucleic acid (RNA) with other molecules. The expected outcomes are to improve prediction capabilities to decode RNA interactions in disease mechanisms, identify novel therapeutic modalities, and improve existing therapies for targeting RNA. This could result in enhanced capacity to design new therapies and potential to optimise RNA targeting molecules for therapeutic applications. 

Applying imaging methods and data analytics to explore the listening brain

This Project aims to understand brain circuits and processes supporting communication in individuals with hearing problems, including those who use devices such as hearing aids and cochlear implants. The potential benefits are that individualised strategies based on real-time brain states estimate algorithms to empower listening and support effective communication. The Project will use brain-imaging techniques‚ including those compatible with listening technologies, including electroencephalogram (EEG), to explore the listening brain. The Project will explore brain changes that arise from hearing loss, how changes in brain function – within and beyond the auditory brain – arise to support listening when hearing is impaired, and how these findings can be used as a part of devices such as cochlear implants that engage the rest of the brain to support an individual's listening. 

Synthetic CT via Generative AI for MR-guided Radiotherapy Planning in the Abdomen and Lungs

This Project will leverage artificial intelligence to develop and validate synthetic computed tomography (CT) from magnetic resonance imaging (MRI) in the abdominal and lung regions. The expected outcomes are an AI-based synthetic CT model, thorough technical and clinical validation and potential patent/licensing opportunities. This may reduce unnecessary ionising radiation of CT in patients and improve treatment efficiency during radiotherapy planning.

Clinical lab automation with AI human robot interface

This Project will develop an AI-based robotic programming interface based on large-language model that allows practitioners, regardless of their technical expertise, to efficiently program and control robots. The expected outcomes are to improve efficiency in designing and deploying clinical lab automation and to expand the use of robotics within laboratories. This may lead to improvements with workflow for clinical lab automation, particularly during high-demand situations like pandemic outbreaks.

Quantifying methane emissions from wastewater treatment

This project aims to quantify methane emissions from wastewater treatment plants. The expected outcomes are improved understanding of methane emissions from within the plant, their spatial and temporal variability, and how they contribute to the total emissions. This may reduce emissions of methane.  

Cyber security risk mitigation for sensor data integrity

This Project will investigate cyber security risk mitigation approaches to secure the integrity of sensor information feeding into critical infrastructure operational systems and digital twins. The expected outcome is the development of guidelines for implementing robust cyber security measures. This may enhance resilience against cyber threats and ensure the integrity of decision-making processes.​

Improving cropping decisions with AI-enhanced weather forecasts

This project will investigate the use of artificial intelligence (AI) to improve weather forecasts and discover how AI forecasts can advance farming decisions by coupling with crop models and smart farming tools. This is an exciting opportunity to develop or integrate novel AI-enhanced weather forecasts into real world modelling applications, for example in the sugarcane industry. With research being undertaken alongside real farm advisors, your research can help industry to optimise resource use and enhance overall farm productivity while minimising environmental impact.

Resilient and quantum-safe threshold cryptography

This Project will design quantum-safe threshold encryption and/or authentication algorithms. The expected outcome is the design of methods, techniques and their software prototype to implement quantum-safe threshold encryption and/or authentication algorithms. The potential benefit is to enhance the security of Australian critical infrastructures, safeguarding them against quantum attacks.