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Bezares (numerical relativity), Dr Stephen Green (gravitational waves, data analysis including machine learning, black holes), Dr Laura Sberna (gravitational waves, black holes, and environmental effects
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qualification/experience in a related field of study. The successful applicant will have expertise in statistical modelling, epidemiology or machine learning and possess sufficient specialist knowledge in
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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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. 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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/or machine learning methods, and an interest in applying these tools to urban and housing policy questions. The Fellow should demonstrate potential for producing high-quality research and a strong
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UKESM1 or similar models, advanced data analysis and machine learning, would be advantageous. Grade E: You will be near completion of a relevant PhD or have equivalent research experience, and be able
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, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded methodology project
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techniques to enable large-scale data search across Personal Online Datastores (pods) hosted on distributed pod servers, addressing both keyword-based search and SPARQL querying. EPRESSO will build on and
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or machine learning to complex data. The successful candidate will have (or be nearing completion of) a PhD in a relevant field such as polymer science, materials engineering, or mechanical engineering
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30 Aug 2025 Job Information Organisation/Company UNIVERSITY OF SURREY Research Field Physics Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Established Researcher (R3