11 affective-computing-"https:" "https:" "https:" "UCL" "UCL" Postdoctoral 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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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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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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) Country United Kingdom Application Deadline 19 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
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, Psychology and Neuroscience (IoPPN). The centre aims to better understand the complex interrelationships between society and mental health, with a commitment to: Ensure that the impact of social context is
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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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to apply cutting-edge techniques, to address fundamental questions in immunology. You will design and conduct experiments, analyse complex datasets, and contribute to high-impact publications in a
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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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emerge, spread, and unequally affect different individuals and population groups. Outcomes of this research will help advance the development of more equitable, spatial data-driven approaches to public