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at the John Curtin School of Medical Research (JCSMR), within the ANU College of Science and Medicine. This role will lead the development of advanced deep learning frameworks—including graph neural networks
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the WATOC Dirac Medal. As the successful candidate, you will contribute to the design and implementation of AI models that integrate quantum mechanical theory with deep learning, enabling rapid and
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: Bayesian Machine Learning – Led by Dr Thang Bui, this project focuses on sequential decision-making and bridging deep learning theory and practice. Applicants with expertise in probabilistic modelling
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degree in mathematics, strongly encouraged to apply. Experience and demonstratable knowledge in deep learning and one or more of the following: transformer networks, implicit neural functions, graph neural
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PhD in Computer Science, Engineering or other Machine Learning-related field. • Programming experience in python, C++ or other relevant language and experience in deep neural networks • Strong
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in sequential decision-making approaches such as Markov Decision Processes, reinforcement learning, deep learning, or adaptive management. You have a strong track record of research publications and
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. The Faculty hosts the Australian Institute of Health Innovation, an internationally acclaimed powerhouse researching health systems, e-health, and patient safety. In learning and teaching, the Faculty offers a
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in conducting human behavioural experiments or human-centered field studies. Demonstrated experience in using machine learning, such as deep learning for image processing, or natural
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 10 days ago
deep learning theory and practice. Applicants with expertise in probabilistic modelling, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine
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neurocritical care research The Opportunity We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis