10 machine-learning-"https:" "https:" "https:" "https:" "https:" Fellowship positions in Australia
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manufacturing principles. Experience with machine learning methods and integration into hybrid modelling systems Demonstrated ability to clearly communicate research concepts and results in high-quality journal
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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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evaluating the efficiency and accuracy of both physics-based models and machine learning techniques, leveraging high-performance computing resources. The role will involve collaboration with leading
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
research labs, and develop teaching and science communication skills. The Person We are looking for a qualified computer scientist or computational linguist with demonstrated expertise in training large
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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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-sensor hyperspectral data for crop disease detection and monitoring. Develop machine learning or physics-informed models to retrieve reliable spectral and/or biophysical features, from multi-scale
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development. Familiarity with software development lifecycle including design and documentation of software architecture, testing/debugging skills, and version control. Experience applying machine learning
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framework to identify and prioritise components suitable for metal additive manufacturing. Applying AI, data analytics and machine learning to evaluate 2D and 3D design data. Collaborating with defence
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closely with researchers and developers, you will help identify challenges, propose solutions, and improve user interfaces based on feedback and testing. You can learn more about the Australian Internet
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and standing recognised by the University/profession as appropriate for the relevant discipline area (e.g., AI/Machine Learning, Bioinformatics). A proven track record of research and scholarly