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We are seeking a full-time Postdoctoral Research Assistant in Physics-Based Modelling of Advanced Batteries to join the Department of Engineering Science under the supervision of Prof Charles Monroe
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We are seeking a full-time Postdoctoral Research Assistant in Physics-Based Modelling of Advanced Batteries to join the Department of Engineering Science under the supervision of Prof Charles Monroe
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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enable the full exploitation of next-generation observations using Exascale computing, i.e. leading the research in solar/stellar physics for many years to come. We are seeking a highly motivated Research
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requirements, including salary thresholds which are applicable to some visas. Person Specification Essential Criteria: Qualifications 1. A PhD (or be close to submission) in Computer Science or a related subject
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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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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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across disciplinary and cultural boundaries. Completed doctoral/PhD studies in Physics, Theoretical Chemistry or Computer Science, or you expect to complete them in the near future. Established experience
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schizophrenia-related symptoms in animal models (mice), in the context of a collaborative project with clinicians and computational scientists. This project will be supervised by Prof Oscar Marin and Prof Beatriz
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clinicians and computational scientists. This project will be supervised by Prof Oscar Marin and Prof Beatriz Rico. Candidates should have strong experience in stereotaxic surgeries and Electrophysiology