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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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: Developing and deploying machine learning models (e.g. graph neural networks, neural force fields, diffusion models) for molecular property prediction and molecular generation. Integrating quantum chemistry
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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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as required. Demonstrated high level of written and oral communication skills. Preferable Experience in eukaryotic cell culture/tissue culture Expertise with advanced graphing and/or data analysis
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learning and one or more of the following: transformer networks, implicit neural functions, graph neural networks and/or probabilistic graphical models; and causal inference. • An outstanding publication
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available for two years. Keywords: Geometric Deep Learning, in particular Graph Neural Networks, Deep Reinforcement Learning, Generative Modelling, in particular Denoising Diffusions, Combinatorial
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. Demonstrated high level of written and oral communication skills. Preferable Experience in eukaryotic cell culture/tissue culture Expertise with advanced graphing and/or data analysis software (Prism, Origin Pro