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team to drive innovation in plant breeding. Key responsibilities will include: Research: Conduct and publish high-quality research, develop a coherent research program, and actively pursue competitive
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2 x full time, 3-year fixed term positions, located on the Camperdown Campus at the School of Mathematics and Statistics Opportunity to drive research in computational pure mathematics through
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Although not required to apply, support and co-investment from a university or institute partner contributes to 25% of the application selection criteria. Any form of support and co-investment should be detailed in the application form. Type of assistance may include monetary or in-kind...
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theory, ergodic theory, differential geometry, data science, and/or machine learning. Implement algorithms that efficiently analyse dynamical systems arising from idealised models or data. Collaborative
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algorithms and techniques and design, implement, test, and maintain software/tools embodying those methods. You will prepare and submit grant proposals to external funding bodies. This position will also
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planning algorithms for GPS-denied lunar environments and extreme operational conditions stochastic optimisation frameworks for mission-critical decision-making under uncertainty Research areas and technical
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Lead cutting-edge computer vision research and deployment to advance traffic video analytics and real-world impact. Full-time appointment on a fixed term basis for two years. Base salary range
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Job no:521360 Work type:Full Time Location:Crawley Categories:Arts, Business, Education, Law Lead cutting-edge computer vision research and deployment to advance traffic video analytics and real
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for the Australian Grains Industry (AAGI) program. The ideal candidate will be an expert in hyperspectral remote sensing with significant experience in data science for geospatial data analytics. This research project
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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
to climate, health, and environmental challenges. Strong candidates will have experience in ML algorithms, human-centered ML, or NLP. Supported by an ARC Future Fellowship and CSIRO-NSF project. Computational