187 fully-funded-phd-program-computer-science-eth Postdoctoral positions at University of Oxford
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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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the Department of Engineering Science at the University of Oxford. The post is funded by the Oxford Martin Programme on Circular Battery Economies. It is fixed term up to December 2027. You will undertake
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and leading a programme of numerical simulations relating to all aspects of our research on P-MoPAs; using particle-in-cell computer codes hosted on local and national high-performance computing
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annum inclusive of Oxford University weighting Potential to under fill at grade 06RS: £34,982-£40,855 per annum inclusive of Oxford University weighting The Department of Computer Science seeks to employ
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project will involve both remote-sensing and field-based observations and data collection. It will provide outputs to the World Bank CAWEP (Central Asia Water Energy Power) programme to aid the design
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application of new methods, ensuring they are kept fully up to date with progress and difficulties in the research projects. It is essential that you hold a PhD/DPhil (or close to completion) in a quantitative
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We are seeking a well organised and self-motivated researcher to work on the Faraday Institution funded SOLBAT and/or LiSTAR projects, reporting to Prof. Mauro Pasta. Applicants must hold PhD/DPhil
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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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leading academic and industry experts, and an active academic/industry exchange program that aims to accelerate career development for the postholder employed on the project. About you The postholder should
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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