126 parallel-computing-numerical-methods Postdoctoral positions at University of Oxford in United Kingdom
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of collaborative projects, working closely with clinicians, imaging experts, and computational scientists across the Oxford–Novartis Collaboration for AI in Medicine. You must hold a PhD/DPhil in Statistics
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Colorectal Cancer - Stratification of Therapies through Adaptive Responses (CRC-STARS) programme, developing and applying cutting-edge mathematical methods to spatial transcriptomics imaging data in order to
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health. Specifically, our approach combines finite element modelling and medical image analysis. Our finite element brain models are based on tissue segmentation and our numerical simulations are validated
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support a high-value materials characterisation programme as a postdoctoral researcher. The ability to think outside the box with creativity, along with having the drive and ambition to develop those ideas
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and numerical modelling, as well as the development and construction of a new mm facility, The Africa Millimetre Telescope, in Namibia. The successful applicant will be based in Oxford and work
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Telescope. You will also have the opportunity to teach. You should hold a PhD (or close to completion) in a relevant area of astrophysics or physics. Experience in performing numerical simulations in
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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programme grant with partners across the UK to facilitate the use of hydrogen for aviation, and in particular the icing vulnerability of heat exchangers and parts of the airframe. You will work to generate
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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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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will