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Field
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. The successful candidate will contribute to a Gates Foundation funded project focused on developing and applying advanced spatial and spatio-temporal statistical methods to inform disease mapping and control
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measurable outcomes and is reflected in a growing national and often incipient international reputation Plan, design and co-ordinate research activities and programmes Contribute to the development of research
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United Kingdom Application Deadline 10 Jan 2026 - 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
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Fellowship is a career development post, designed to enable an outstanding early career academic to undertake an independent, self-directed programme of research that substantially develops or is different
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contribution to the economic, social and cultural development of Northern Ireland. Our core business activities are teaching and learning, widening access to education, research and innovation and technology and
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research focuses on Materials physics, Quantum technology, Soft & living matter, and Advanced energy solutions. Topics extend from fundamental research to important applications. We educate future
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collaborative nature of the programme. Based within the Data-driven Biology Group, the postholder will develop and validate AI and data science tools for multi-cancer risk prediction models using population-scale
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collaborative nature of the programme. Based within the Data-driven Biology Group, the postholder will develop and validate AI and data science tools for multi-cancer risk prediction models using population-scale
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scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across five Departments. About the role
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of Research Excellence (CRE). These Fellowships will provide support (personal salary, access to scientific support posts, and consumables) for successful candidates to prepare, within the timeframe