515 parallel-computing-numerical-methods-"Prof" Postdoctoral positions in United Kingdom
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develop methods for the recombinant production of post-translationally modified structural proteins, investigate their effects on material assembly and properties, and design new, functional materials. In
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work closely with Prof. Hanna Kienzler, Prof. Stephani Hatch, and Dr Rebecca Rhead as part of the Centre’s ‘Marginalised Communities’ programme. This involves partnering with Black and racially
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numerical modelling. Ability to participate in research meetings to troubleshoot research problems and discuss the direction of research. Skills Fluency in at least one scientific computer language (e.g., C
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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This post is a postdoctoral research assistant role within Prof Robert House’s Group in the Department of Materials. The post will be fixed-term until 31 March 2027 (with potential to extend until
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. The Role Applications are invited for a Postdoctoral Research Associate position in the Department of Engineering, with a focus on undertaking both experimental and numerical studies within the hydrogen
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We are seeking a full-time postdoctoral researcher to join Prof Cathy Ye and Prof Wei Huang research groups at the Department of Engineering Science (Headington/ Begbroke Oxford). The post is
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on evaluating the abilities of large language models (LLMs) of replicating results from the arXiv.org repository across computational sciences and engineering. You should have a PhD/DPhil (or be near completion
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are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods
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excellent computational skills. The post is attached to Prof. Eric French's Montague Burton Professorship. The research aims at exploring and understanding the drivers of medical spending, and how medical