423 algorithm-development-"Prof"-"Washington-University-in-St"-"Prof" Postdoctoral positions in United Kingdom
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methods in schools, focus groups, interviews and surveys with students, parents and education stakeholders. The successful applicant will be expected to lead and develop qualitative research activities
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profile development, combining method development, application to real-world problems, and collaboration with experimental groups. Your project will complement ongoing work by other members in the group
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class of signalling molecule that acts during embryonic development to generate a variety of cell states. In response to distinct threshold levels of morphogen signalling, cells follow different fates and
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to the development of digital enablers for authentic real-time performance data and responsible decision-making, by putting user needs at the centre. The successful candidate is expected to: shape and engage in
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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing
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on the development of a computational setup for fiber-enriched materials design within the Processing-Structure-Properties-Performance (PSPP) framework under the joint supervision of Assistant Professor Sergei Khakalo
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practices. Durham University is committed to the Concordat to support the career development of researchers. For further information please visit the Research Staff web pages on https://www.durham.ac.uk
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in Cambridge. The mission statement of the group is "developing statistical methods to use genetic variation to answer clinically important questions about disease aetiology and prevention". The three
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interpretation of all data, maintaining records and databases, drafting technical/progress reports and papers as appropriate. 3. Develop and enhance your research profile and reputation and that of the School
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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing