QLD

Enhancing sustainable land management practices through natural capital profiles

This project addresses knowledge gaps in environmental sustainability and social marketing, focusing on river health and sustainable land management practices via co-creation and adoption of Natural Capital Profiles. The expected outcome is to extend existing frameworks in social marketing, with a particular emphasis on the Co-Create – Build – Engage (CBE) process, to design more user-friendly behaviour change solutions for improved river health and land management practices. The project will potentially increase the adoption of Natural Capital Profiles by landholders, enabling healthier river ecosystems and better land management.

Identifying serum biomarkers in PFAS serum concentration using metabolomics

This project investigates the health impacts of PFAS exposure in firefighters using advanced metabolomic techniques to identify biomarkers. The expected outcome is the development of new biomarkers for PFAS exposure, enhancing health diagnostics and preventive measures. This research will potentially lead to improved health risk assessments, better regulatory policies, and enhanced safety for workers exposed to hazardous substances.

Valuing non-crop vegetation in horticultural landscapes of Australia

This project will explore the extent to which areas on farms such as semi-natural vegetation, tree plantings, woodlands, and shelterbelts benefit producers through ecological mechanisms, such as enhancing pollinators or pest predators along with broader aesthetic and Indigenous cultural benefits. The outcome of this project will provide an improved understanding of the scale and relative importance of these benefits in the agricultural production landscape of northern New South Wales. This project will directly support horticulturalists in the region and guide future policy.

Quantum-AI for food security and student wellbeing

This project develops quantum-AI tools to optimise urban hydroponic food systems and evaluate their therapeutic impact on student well-being. The expected outcome is to create quantum-reinforced AI algorithms for resource-efficient hydroponics and evidence-based frameworks for integrating green space exposure for improved student wellbeing. This project will potentially enhance urban food resilience, reduce resource waste, and create scalable mental health interventions, advancing national sustainability and education priorities. 

Building responsible AI: Co-designing knowledge transfer solutions using generative AI

This project will bridge the gap between the principles of responsible AI and their measurable practice, by developing AI knowledge tools to empower end-user community groups. The expected outcomes are to build insights and develop AI tools for information dissemination and knowledge transfer. The potential benefit is to produce responsible AI solutions to help disability groups connect, communicate, share and learn.

AI for Early Detection of Neurodegenerative Disorder in Elderly

This Project aims to develop outcome measures for early detection of neurodegenerative disorders using artificial intelligence (AI) and various sensing modalities, offering personalised support to older adults. The expected outcome is the creation of AI algorithms to detect early signs of neurodegenerative disorders in older adults living independently at home. The potential benefit is early detection of neurodegenerative disorders in older adults, improving quality of life and effective disease management.

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.  

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.

Fingerprinting critical minerals development in continental margins

This project will study how critical minerals develop in the Andean-type plate margins through case studies in eastern Australia. The expected outcomes are results that characterise signature minerals in a polymetallic minerals province in Far North Queensland. This may result in supplying new data-driven mineralisation models for key exploration regions.