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focuses on scalable, AI-driven decision-making in collaboration with defence industry partners and an academic partner at the University of Melbourne. One role focuses on machine learning for decision
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journals, Supervision of PhD and undergraduate research students Make use of ice sheet models, machine learning and published field datasets to reconstruct the evolving post-LGM Antarctic Ice Sheet. Initiate
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focus on processing and utilising machine-learning techniques to analyse large volumes of data from sensors installed in Phase 1. The aim will be to merge the QC points and tracking system developed in
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: Using big data insights to optimise the manufacturing process The second phase of this project will focus on processing and utilising machine-learning techniques to analyse large volumes of data from
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, simulations, AI, and machine learning applied to proteins. A track record of research outputs, including publications and presentations at national or international level. Excellent communication and
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agricultural science with a quantitative focus (or an equivalent discipline) expertise in statistical and machine learning approaches, with the ability to apply advanced methods to complex environmental and
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Intelligence or Machine Learning, with demonstrable analytical skills. Excellent research record evidenced by first-author publications in strong international journals and conferences. Proven experience in
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(e.g., Docker, Kubernetes, cloud/edge environments). Demonstrated expertise in AI, distributed computing, machine learning, or systems software design. Strong background in software engineering
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
PhD in seismology, geophysics, computer/data science, or planetary science. You will have demonstrated expertise in global seismology, particularly relating to the Earth’s core, core–mantle boundary
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. Experience in molecular modelling, simulations, AI, and machine learning applied to proteins. A track record of research outputs, including publications and presentations at national or international level