Mid-Career Industry Fellowships - Grant ID: IM230100002
Funder
Australian Research Council
Funding Amount
$1,056,049.00
Summary
Artificial intelligence empowered multi-modal biomedical imaging. This Industry Fellowship aims to transform biomedical imaging using artificial intelligence with world-leading industry partners. The project expects to make a major advance in multi-modal Magnetic Resonance Imaging and Positron Emission Tomography image reconstruction for robust, accurate and efficient imaging. This project timely addresses industry needs with novel solutions and will establish a technology roadmap to inform and ....Artificial intelligence empowered multi-modal biomedical imaging. This Industry Fellowship aims to transform biomedical imaging using artificial intelligence with world-leading industry partners. The project expects to make a major advance in multi-modal Magnetic Resonance Imaging and Positron Emission Tomography image reconstruction for robust, accurate and efficient imaging. This project timely addresses industry needs with novel solutions and will establish a technology roadmap to inform and de-risk future research and development in image reconstruction. The project outcomes should provide benefits to Australians with cost-effective imaging and benefits to Australia's biomedical industry with well-aligned intellectual properties and training of future scientists with industry knowledge.Read moreRead less
Mid-Career Industry Fellowships - Grant ID: IM230100025
Funder
Australian Research Council
Funding Amount
$747,126.00
Summary
Using the blackleg fungus as a model for maximising fungicide efficacy. Resistance to chemicals impacts the ability to control many diseases across many crops. This project aims to identify key epidemiological factors contributing to fungicide resistance in an emerging model system, blackleg disease of canola, using innovative approaches. The outcomes of this research will be management strategies for minimising the risk of evolution of fungicide resistance, a key industry need. This will also e ....Using the blackleg fungus as a model for maximising fungicide efficacy. Resistance to chemicals impacts the ability to control many diseases across many crops. This project aims to identify key epidemiological factors contributing to fungicide resistance in an emerging model system, blackleg disease of canola, using innovative approaches. The outcomes of this research will be management strategies for minimising the risk of evolution of fungicide resistance, a key industry need. This will also enhance interdisciplinary collaborations through combining field and molecular research. These management strategies will provide significant economic benefits by ensuring increased canola yields, whilst providing health and environmental benefits through minimisation of unnecessary use of fungicides.Read moreRead less