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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
centre for research in artificial intelligence and machine learning, computer systems and software, and theoretical foundations of computing. We span traditional and modern thinking, connecting decades
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; ongoing learning and development opportunities to grow your career; an inclusive and supportive culture and environment to work in, both online and on campus. Who are we? Deakin is a cutting-edge public
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-renewable-energy-engineering Skills & Experience: A PhD in Computer Science or a related field. Thorough theoretical background in machine learning and deep learning. Demonstrated experience in developing
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the direction of A/Prof Claudia Szabo in the School of Computer and Mathematical Sciences at the University of Adelaide. The project is a collaboration with Defence Science and Technology Group, within the Combat
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the Faculty, the Department of Electrical and Computer Systems Engineering (ECSE) offers internationally acclaimed programs in power systems, telecommunications, electronics, robotics and biomedical engineering
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peer-reviewed publications, while providing senior-level expertise to support and mentor internal teams. A vital responsibility includes guiding emerging science-practitioners (Clinical Psychology PhD
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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
Integrated Planning & Learning and Reinforcement Learning in non-deterministic and partially-observed scenarios. The methods will be evaluated on physical robots. The ideal candidate would have: A PhD (or
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experience contribute to ongoing translational research program related to the application of statistical and machine learning methods in reproductive and perinatal medicine using both clinical quality
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simulations using DFT (particularly of surface processes); kinetic Monte Carlo simulations; molecular dynamics simulations; classical and machine-learned force fields. Highly developed skills in scientific
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for uncertainty quantification in learned computer vision. The person should have a PhD in Computer Vision or a closely related field, and a demonstrated strong track record in this field. This should include