291 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" research jobs in Australia
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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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, 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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discover them The Opportunity The Department of Electrical and Computer Systems Engineering at Monash University is seeking a motivated Level A Research Fellow for a 2 year research-only appointment. A Level
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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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monitoring approaches (e.g., machine learning, real-time sensing). Sponsorship / work rights for Australia You must have unrestricted work rights in Australia for the duration of this employment to be eligible
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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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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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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 20 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
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density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data, including with the use of machine learning use this knowledge to design