105 computional-geometry-algorithm Postdoctoral research jobs at University of Oxford
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Join the Oxford Martin Programme on Forecasting Technological Change at the University of Oxford, led by Dr François Lafond, Prof J. Doyne Farmer, and Prof Max Roser. This pioneering programme aims
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interdisciplinary research programme investigating how immune mechanisms contribute to psychiatric and neurological disorders. The project combines human induced pluripotent stem cell (iPSC)- derived neuronal and
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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proven expertise in seismic data processing and analysis, knowledge of volcanic/ geothermal processes, strong quantitative skills, and proficiency in Python for scientific computing. You should be
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Postdoctoral Researcher. The group aims to identify, understand, and develop therapies for rare genetic disorders. The group is primarily computational but partners with multiple international labs (including
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Lives with Linear Accelerators) project, which aims to leverage technologies developed for particle physics, computer vision and robotics into a novel end-to-end radiotherapy system as an essential
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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. The post-holder will be one of six centre-funded postdoctoral researchers delivering on projects that form our core research programme. They will be a cornerstone of the centre, collaborating across our
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leadership skills as a postdoctoral researcher. This position is for 24 months at Grade 7. You will be working in either the rapidly emerging area of functional material photonics in non-von Neumann computing