543 parallel-computing-numerical-methods-"Simons-Foundation" positions at University of Oxford in United Kingdom
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We are seeking five full-time Postdoctoral Research Assistants to join the Computational Health Informatics Lab at the Department of Engineering Science, based at the Institute of Biomedical
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the performance of lithium ion technologies. To support the programme, the post holder will be required to carry out research on characterisation of battery degradation, with a particular focus on the application
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Oxford-DeepMind Graduate Scholarship (Computer Science) The Oxford-DeepMind Graduate Scholarships (Computer Science) are available for applicants to any full-time DPhil course within, or affiliated
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of marketing materials and contribute to applicant yield and retention initiatives. Take ownership of specific recruitment or programme-related projects and events, managing budgets and timelines. You will
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well as generating and interpreting high-quality visualisations of complex pQTL data, such as Manhattan plots, concordance scatter plots and Miami plots. You will also apply advanced statistical genetics methods
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, infectious disease epidemiology, systems immunology, computational biology etc) and have experience using statistical methods and machine learning tools, and in developing reproducible informatics pipelines
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workshops or fabrication facilities. You must also have experience in high technology research and development and Experience of Computer Numerical Controlled machining. You must also have experience in
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Brian Nicholson (Cancer Theme). The successful applicant will be Stats lead for the EBHC DPhil programme and Methodological lead for the Cancer Theme. Responsibilities will include providing strategic
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settings. We are seeking a highly motivated postdoc to conduct research into this fast-moving area. Directions may include investigating quality evaluation methods for multi-agent systems, attack surfaces
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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