256 computer-"https:"-"https:"-"https:"-"https:"-"Leeds-Beckett-University" Postdoctoral positions in United Kingdom
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Health Translational Research Collaboration and which sits within a ground-breaking new Centre: Civic Health Innovation Labs (CHIL). M-RIC is an ambitious programme of work jointly delivered between
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of the atmosphere for research purposes. An excellent knowledge of atmospheric physics. A strong experience in a scientific computing and data visualisation language. The ability to work independently and as part of
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University (USA), and Google Deepmind (London). About the role The PDRA will lead the development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for
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funded by the Leverhulme will collaborate with the PDRA on parts of the project. The candidate should be able to provide evidence of expertise in visual psychophysics and should have strong computing
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a project investigating prehabilitation for cancer populations in collaboration with the Cancer Treatment Outcome Programme at the Country Durham and Darlington NHS Trust. Prehabilitation means
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archaea, many of which also use histones as major chromatin building blocks, and non-model bacteria. In the lab we combine a variety of computational and experimental techniques, including phylogenomics
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, psychology, computational neuroscience, biomedical engineering, or a closely related quantitative STEM discipline. A strong background in cognitive, behavioural, and/or systems neuroscience, with relevance
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sensing. are essential as well as strong computing skills, including the knowledge of UNIX/Linux, Fortran, Python, or other high-level languages. The post is full time and fixed term for 18 months
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part of an interdisciplinary team working across physical and computer science to develop new pathways to the design and discovery of inorganic materials as part of the Leverhulme Centre for Functional
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Colorectal Cancer - Stratification of Therapies through Adaptive Responses (CRC-STARS) programme, developing and applying cutting-edge mathematical methods to spatial transcriptomics imaging data in order to