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, Mathematics, or related fields Evidence of the ability to conduct high-quality research and produce publications in top-tier venues Confidence in understanding and handling of complex mathematical ideas. Firm
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partnership to achieve excellence in public and global health research, education and translation of knowledge into policy and practice. This post involves combining mathematical models with detailed data from
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Job id: 090085. Salary: £43,205 - £50,585 per annum, including London Weighting Allowance. Posted: 24 May 2024. Closing date: 09 June 2024. Business unit: Natural, Mathematical & Engineering Sci
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: Natural, Mathematical & Engineering Sci. Department: Informatics. Contact details:Martin Albrecht. [email protected] Location: Strand Campus. Category: Research. Job description The department
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linkage purposes to better characterise health outcomes and their sub-types. To be considered, you must hold (or close to completion of) a PhD in computer science, mathematics, software engineering or
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the globally-distributed tskit-dev team. It is essential that you hold a PhD/ DPhil (or close to completion) in a quantitative science subject, together with experience in mathematical population genetics, in
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teaching and supervising graduate students, as well as the ability and flexibility to teach across a range of topics in probability theory and its applications and mathematics and statistics in general at
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)) models are used at all stages of pre-clinical and clinical development, but they are based on mathematical and statistical principles dating from the 1970s. Developing these pharmacometric models remains a
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of researchers with backgrounds in public health, psychology, operational research, mathematics, systems engineering, behavioural science, social policy, demography and economics. The group attracts significant
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the ability to conduct and complete research projects, as witnessed by published work in machine learning on the specific topics, and strong mathematical skills in probability and statistics. Good knowledge