681 parallel-computing-numerical-methods-"Prof" Fellowship research jobs in United Kingdom
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Programme Exceptional starting annual leave entitlement, plus bank holidays Additional paid closure over the Christmas period Local and national discounts at a range of major retailers As an equal
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a specified range of activities within an established research programme and/or specific research project. We are looking for a Research Fellow to work in the area of polymer characterisation
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. The successful candidate will join a large and diverse group of researchers covering nuclear structure physics, nuclear astrophysics, applications of nuclear physics and nuclear theory. The candidate's programme
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2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a
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Jan 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe Is the Job related to staff position within a Research Infrastructure? Yes Offer Description Faculty of Environment
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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics
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(STFC, Daresbury), Prof. Jonathan Tennyson (University College London) and Prof Michael Charlton (Swansea). The Research Fellow will work on the development of methods and computer programs adapted
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, representing excellent value for money This full-time post is funded by the NHS Cancer Programme with support from SBRI Healthcare and the Accelerated Access Collaborative and is available from 05th January 2026
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directed to Prof James Gates gates@southampton.ac.uk Applications for Research Fellow positions will be considered from candidates who are working towards or nearing completion of a relevant PhD
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where