296 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" research jobs in Australia
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the Position Description for this role. Applications Close Monday 19 January 2026 11:59 PM Where to apply Website https://www.timeshighereducation.com/unijobs/listing/405304/postdoctoral-resear… Requirements
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opportunities for student supervision and career development. For more about the Fairlie Group please visit - https://imb.uq.edu.au/research-groups/fairlie . Key responsibilities will include: Research
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, rotating machines, system integration and electrical reticulation/protection. This role will also see you work collaboratively with a multidisciplinary team to advance renewable energy technology through
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Australia Curtin University The University of Notre Dame Australia (Fremantle Campus) How to Apply Apply online via the Forrest Research Foundation Creative Fellowships page: https://forrestresearch.org.au
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, measure transport and machine learning on developing a novel mathematical framework for identifying reduced dynamical models of high-dimensional complex multi-scale systems. The project will develop fast
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machine learning, big-data analytics, and data-driven approaches to optimise composition–process–property relationships. Key responsibilities will include: Research: Conduct additive manufacturing research
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related discipline): Computer Science, Artificial Intelligence, or Machine Learning Economics or Econometrics (particularly applied micro, behavioural, or decision-focused modelling) Applied Mathematics
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experience in: Radial velocity, stellar, and/or exoplanet spectroscopy studies; and/or astronomical instrumentation or observing programmes Machine learning in physical science, using Jax, PyTorch, and/or
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. This pivotal role sits at the heart of the Strategic Alliance between Open Door and Military and Emergency Services Health Australia (MESHA), strengthening national research capability and driving meaningful
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 13 days ago
machine-learning methods to investigate the deep-time controls on copper mineralisation. The role will involve developing reproducible computational workflows, generating predictive maps of copper