22 parallel-computing-numerical-methods Postdoctoral positions at University of Oxford; in United Kingdom
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statistical and computational methods designed to use “big data” and to address questions of direct or indirect relevance to common complex diseases and disorders. The appointee will join the group of Professor
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About the role We are seeking a full-time Postdoctoral Research Assistant to join the Numerical Analysis research group at the Department of Engineering Science (Osney). The post is funded by Rolls
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scientists, forming small teams focused on ambitious, ‘blue sky’ research for novel methods development relevant for drug discovery analysis pipelines, trial design and operational efficiency. Led by Professor
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for this post. The successful candidate will be required to develop a personal research programme in theoretical cosmology (which may include numerical modelling and/or data analysis), interacting with faculty
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multiple sclerosis under different treatment exposures. You will contribute to delivery of collaborative projects, working closely with clinicians, imaging experts, and computational scientists across
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Transcriptomics and Multiplex Immunofluorescence platforms. You will develop computational methods for identification of discriminative spatial interactions of therapeutic response, and develop skills in
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and numerical modelling, as well as the development and construction of a new mm facility, The Africa Millimetre Telescope, in Namibia. The successful applicant will be based in Oxford and work
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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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partners, you’ll turn these insights into practical methods for smarter testing and control. You’ll need to have expertise in modelling and simulation of dynamic systems, strong programming skills, and the
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deductive qualitative research methods (including e.g. Framework Analysis). Experience/knowledge of child anxiety presentation, measures and intervention and of intervention co-design/co-adaptation would be