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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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infrastructure planning. This fixed-term project role plays a critical part in shaping future-ready learning environments through data-informed strategy. The Space Modeller will be a forward-thinking analyst who
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will engage in software development using deep learning, natural language processing, and large language models (LLMs). This position is embedded within a commercialization initiative focused on
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 21 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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Simulation group to apply classical Molecular Dynamics and Machine Learning approaches for development of a new class of hybrid polyphenol-lipid nanoparticles with tuneable internal structure and exploration
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data, spatial modelling, multivariate statistics and/or machine learning, and relevant coding languages (e.g. R, Python), including a sound understanding of FAIR data principles, data management and
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
at the Australian National University. The Fellow will lead independent, high-impact research in advanced machine learning and hybrid modelling for genomics and cellular processes, contributing directly to the
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, and interpretation of environmental and/or ecological data. Research outputs such as technical reports and scientific papers in peer-reviewed journals. Computer skills including the use of Microsoft
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an outstanding environment in which to develop innovative research in mathematical and statistical data science, with opportunities for collaborations with machine learning and bioinformatics researchers in
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-atomic potentials using a combination of classical and machine-learning (ML) approaches (and a new hybrid method recently developed in our group). Some of the types of simulations that will be performed