186 computational-physics-"https:"-"https:"-"https:" Fellowship positions in Australia
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Agroecology Team, you’ll work with a multidisciplinary group of entomologists, geneticists, ecologists and industry partners—supported by world-class laboratories, high-performance computing and specialist
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 30 days ago
the Science in Australia Gender Equity (SAGE) program and a platinum member of the Australian Network on Disability. We welcome applications from people of all backgrounds and identities and from individuals
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Computer Science, Applied Mathematics/Statistics, Robotics, Physics, or related discipline, with an excellent academic record. Demonstrated expertise in computer vision and machine learning, including object
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will streamline how experts and stakeholders process, interpret and access complex, high‑volume information, and unlock new capabilities in modelling, data integration and knowledge retrieval for current
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type: Domestic and international students Study stage type: Current study, Alumni Study area: Business and economics Need help understanding the process? Visit our scholarship guide Application How
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contribution of 17% superannuation applies. Full-time, fixed term position for 13 months. We are seeking a Postdoctoral Research Fellow (Level B) to join the School of Computer and Mathematical Sciences
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School of Electrical Engineering and Computer Science Full-time (100%), fixed-term position for up to 3 years Base salary will be in the range $114,824.05 - $136,048.72 + 17% Superannuation
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which provides rural clinical training for WA medical students from UWA, The University of Notre Dame and Curtin University. Initiated in 2002, this program has grown to encompass 15 rural sites and one
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Alexandra Hospital About This Opportunity Join a world-class research environment at The University of Queensland as a Research Fellow or Senior Research Fellow supporting the Physical and Mental Health
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in supporting Australia’s transition to green ironmaking by developing a quantitative framework that connects impurity content, process parameters and microstructural evolution to scalable, low