125 parallel-computing-numerical-methods-"Prof" Postdoctoral positions at University of Oxford in United Kingdom
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We are seeking a highly motivated Postdoctoral Research Scientist with a strong background in human induced pluripotent stem cell (iPSC) differentiations and computational analysis to join Dr
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mechanism design. The project will involve close collaboration with project teams at Imperial College London, the Edinburgh Parallel Computing Centre (EPCC) and the Luxembourg Institute of Science and
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, reporting to Prof. Mauro Pasta. Applicants must hold PhD/DPhil in Materials Science or Chemistry (or be close to completion), together with relevant experience in the field of beyond Li-ion batteries and have
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focus on ambitious, ‘blue sky’ research for novel methods development relevant for drug discovery analysis pipelines, trial design and operational efficiency. Led by Professor Chris Holmes, and with
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and application For more information about these positions please contact Prof. Nynke Dekker, e-mail: nynke.dekker@physics.ox.ac.uk Only applications received before midday 16 June 2025 can be
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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Metabolism (OCDEM) on studies related to circadian rhythms in population health. This post is part of a large, interdisciplinary research programme, offering attractive opportunities to work across
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computational sciences, decision-maker education campaigns, and training the next generations of technology governance leaders. It is one of the few organisations in the world to focus on the governance of AI
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and clinical neuroscience. This project involves development of machine learning methods for mapping the relationships between diffusion MRI (dMRI) and phase-sensitive OCT (PS-OCT) in the same tissue
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Computational Methods for Advanced Research to Transform Biomedicine ( SMARTbiomed ), an international collaboration that integrates large-scale, multimodal biomedical data with advances in statistical and