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involves computer simulations of catalytic and environmental interfaces, aiming at reaching fundamental new understanding of elementary processes at such interfaces. As part of our work, we also seek
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. Please refer to the further particulars document for a full list of the essential knowledge, skills and experience required for the role. Click the 'Apply' button below to register an account with our
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research centre well-known for its close-knit community, friendly atmosphere, and outstanding research support. We are seeking a post-doctoral research associate with experience in computational approaches
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-generation AI hardware (ASIC) accelerators. The UK's Advanced Research Invention Agency (ARIA) is supporting an ambitious programme of work that aims to reduce the the cost of AI by more than 1000x: https
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to understand immune microenvironmental interactions; Integration and interpretation of complex datasets in collaboration with computational scientists You will be expected to take a lead in experimental design
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of the research programme is to develop EHR common data model specifications and to advance knowledge in the field of psychiatry EHR research, including clinical risk prediction modelling. The appointee will work
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techniques. Analyse experimental data using statistical tools and computational methods. Collaboration & Mentorship: Collaborate with interdisciplinary teams of researchers and students. Mentor graduate and
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(if you have not already) and apply online. Please ensure that you upload a 2-page Curriculum Vitae (CV), a covering letter and publications list in the Upload section of the online application. If you
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development. The ideal candidate will have a PhD in a relevant biological subject, together with experience in molecular biology, cell biology and immunology. Familiarity with flow cytometry, vascular biology
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the following documents: Cover letter detailing your research experience and interest in the position. Curriculum vitae (CV) with a list of publications. A brief research statement outlining your past research