12 computing "https:" "https:" "https:" "University of St" research jobs at KINGS COLLEGE LONDON
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20 Jan 2026 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Computer science Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application Deadline
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: The successful candidate will join the Distributed AI (DAI) group in the Department of Informatics, King’s College London. They will carry out research in neuro-symbolic AI, with a focus on using generative and
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- 00:00 (UTC) Country United Kingdom 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
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the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description About us The
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) Established Researcher (R3) Country United Kingdom Application Deadline 12 Jan 2026 - 00:00 (UTC) Type of Contract Other Job Status Part-time Is the job funded through the EU Research Framework Programme? Not
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research scientists. Based across Guy’s, St Thomas’ and Waterloo campuses, King’s Denmark Hill, our academic programme of teaching, research and clinical practice is embedded across five Departments. More
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Deadline 5 Feb 2026 - 00:00 (UTC) Country United Kingdom 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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University (USA), and Google Deepmind (London). About the role The PDRA will lead the development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for
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Neuroscience. The Headache Group was established to improve the lives of those with primary headache disorders through an integrated programme of research, teaching and clinical activity. About the role
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University (USA), and Google Deepmind (London). About the role The PDRA will lead the development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for