14 parallel-computing-numerical-methods Postdoctoral positions at University of London in Uk
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. About You The ideal candidate will have a PhD in a numerate field, be familiar with medical image analysis using deep learning methods, have experience with GitHub and relevant programming languages
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subject area for the research and innovation project and relevant knowledge and experience in geomatics, remote sensing methods (including UAV lidar, satellite and photogrammetry) and spatial analysis including
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-performance or cloud computing environments. Need strong data management and database skills, expertise in clinical phenotyping ontologies and the application of machine-learning/AI methods to biomedical data
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to work on a project investigating mechanosensing in flies (Diptera). This post will focus on using detailed wing geometry models and free flight kinematic measurements in computational fluid and structural
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About the Role The purpose of this role is to provide mixed methods and evidence synthesis research support for a Gates funded project examining the utility of iron preparations for maternal anaemia
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at the William Harvey Research Institute (WHRI , Queen Mary University of London, QMUL ), whose research aims to develop and apply computational tools to identify the genetic determinants of rare Mendelian and
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About the Role This 3 year full-time PDRA position, using advanced transmission electron microscopy (TEM), is part of an exciting major EPSRC-funded Programme Grant, "Enabling Net Zero and the AI
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computational modelling and design optimisation. You will run CFD and fluid-structure-interaction simulations. You will develop models, analyse results and collaborate with partners to inform design. The role
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, to deliver the aims of the programme. The PDRA will join a team working on extracellular vesicles as well as other aspects of inflammation resolution, with close attention to the exploit this science for
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detection models, with a focus on achieving generalisable multimodal understanding in zero-shot settings. About You The successful candidate must have a PhD (or equivalent) in the field of computer vision or