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) implement the COMPAS survey across two waves at St John Ambulance, (c) develop a predictive algorithm that can predict suicidal intentions and behaviours 12 months later, (c) use the algorithm to stratify
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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
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-tracking, pupillometry), cognitive modelling, and regulatory analysis to assess how algorithmic explanations shape human judgement and how existing legal and ethical frameworks align with the evolution
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research methods Desirable: interest in pursuing pathways between industry and academic research Application process To express your interest, please submit an EOI form address to Prof Katie Ellis
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understanding of deep neural networks by exploring the human-understandable meanings of learnt features, the evolutionary dynamics of these features across network layers, and the architectural designs
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about potential research projects, please contact Prof Toby Pavey . For information on how to apply for this scholarship, please contact hdr@qut.edu.au . What happens next? Applicants will be contacted
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: Prof Alisher Kadyrov (a.kadyrov@curtin.edu.au ). Scholarships Email Alert Sign up now
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modelling and simulation of transmission and distribution networks, including benchmarking data models, developing optimal power flow algorithms, and creating state estimation and multi-energy optimisation
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at the University of Adelaide is subject to the execution of a scholarship agreement for the relevant project. Enquiries A/Prof Peter Smitham: peter.smitham@adelaide.edu.au General Enquiries: HDR Industry team
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novel opportunity to automate and improve the frailty assessment process, aiming for greater consistency and predictive accuracy. Aims i) Develop a deep learning algorithm to autonomously detect and