145 high-performance-computing Postdoctoral positions at University of Oxford in United Kingdom
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We are seeking a creative and highly motivated postdoctoral researcher to join the Turing AI World-Leading Fellowship research programme led by Professor Alison Noble. This exciting and ambitious
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research initiative funded by ARIA, titled Aggregating Safety Preferences for AI Systems: A Social Choice Approach. The project operates at the interface of AI safety and computational social choice, and
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record in conducting cross-species research to investigate how cells and circuits in the brain work together to perform computations that support memory. The proposed research will take full advantage
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About the role The Kelly lab is excited to announce a new post-doctoral position in computational biology. This position is funded as part of an international consortium of scientists who
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of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), Oxford As a Postdoctoral Research Assistant in Translational Biology you will be performing laboratory experiments and data analysis to support
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Institute for Molecular and Computational Medicine (IMCM). You will test GSK assets and targets in established models of podocyte and mesangial cell pathology relevant to glomerular diseases. You will
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Jarvis to lead the processing of the MIGHTEE continuum and HI survey data. The role requires a high level of technical expertise in radio interferometry techniques and would help coordinate the processing
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dioxide copolymerization catalysis, including using high-pressure reactors. We seek a candidate interested to join our diverse, multi-disciplinary research team and help us to try to solve these important
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management of sport injuries, with emphasis on safety rather than performance. You will be part of an interdisciplinary team of pioneering researchers, with the primary aim to develop cutting-edge robotics and
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accessibility of the method to enhance user ability to perform analyses in comparative genomics, enable new analyses, and gain new evolutionary insights from data generated using OrthoFinder. The successful