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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
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, with findings of international relevance across health systems facing similar workforce pressures. Integrated PhD Program The project is based in the Centre for Health Economics (CHE), a large and active
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groups in the economic analysis of health and health care. We have the highest concentration of economists working in health in the Asia-Pacific region and the largest Health Economics PhD program in
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concentration of economists working in health in the Asia-Pacific region and the largest Health Economics PhD program in Australia, reflecting the reputation of our researchers and the quality of their mentorship
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to work closely with other leading academics at Monash University, including Professor Carol Propper , A/Prof Terrence Cheng and Dr Danusha Jayawardana . As a candidate in the CHE Integrated PhD Program
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inference. PhD Program The project is based in the Centre for Health Economics, a large and active economics research group within the Monash Business School in Melbourne, Australia. As a candidate in the CHE
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With success stories ranging from speech recognition to self-driving cars, machine learning (ML) has been one of the most impactful areas of computer science. ML’s versatility stems from the wealth
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that occurs within these biological neural networks, so that these networks can be leveraged for AI applications. In addition, you will develop mathematical and computational neuroscience models
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Environmental Engineering Mechanical and Aerospace Engineering Electrical and Computer Systems Engineering Chemical and Biological Engineering Materials Science and Engineering About the Role We are seeking
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analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images