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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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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
expertise in one or more of a broad range of computational methods including but not limited to: machine learning / AI, spatial computing, computational creativity, text encoding, social media analysis
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
and digital methods. Position overview We are interested in candidates with expertise in one or more of a broad range of computational methods including but not limited to: machine learning / AI
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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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data science methods to build explainable and integrated machine learning models that can be utilised by health services to make real-time, data-informed clinical decisions in youth mental health care
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contributions to sea level rise with improved accuracy. You will have a passion for Antarctica and quantitative skills that include programming and machine-learning or numerical ice sheet modelling. As the
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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