105 computional-geometry-algorithm Postdoctoral research jobs at University of Oxford
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clinical trials, and developing personalised models to understand therapy response characteristics. You will contribute to a pioneering tissue-focused research programme aimed at enhancing cure rates
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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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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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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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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