24 computer-science-"Atlantic-Technological-University" Postdoctoral positions 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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11 Dec 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Chemistry Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country United Kingdom
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bioelectrochemistry Experience on computational modelling of iointerfaces Evidence of independent motivation in the formulation, planning and implementation of research activities Wet Chemistry lab work with analytical
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11 Dec 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Juridical sciences Psychological sciences Researcher Profile Recognised Researcher (R2) Established Researcher
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About us Working as part of a world-class academic team based in the Department of Forensic and Neurodevelopmental Sciences at the Institute of Psychiatry, Psychology & Neuroscience (IoPPN
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6 Jan 2026 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field History Philosophy Religious sciences Environmental science Geosciences Political sciences Sociology Ethics in
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24 Dec 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Biological sciences Computer science Mathematics Researcher Profile Recognised Researcher (R2) Established
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19 Dec 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Biological sciences Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country
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and experience: Essential criteria PhD in applied mathematics, statistics, engineering, computational biology, econometrics, or a related discipline. Experience in developing complex models using real