14 assistant-professor-computer-"https:"-"https:"-"Central-European-University" Postdoctoral positions at KINGS COLLEGE LONDON
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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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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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About Us We seek to appoint a Postdoctoral Research Associate in Immunology to join the lab of Professor Patricia Barral. The post will be based at the Centre for Inflammation Biology and Cancer
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conditions. About the role We are seeking a highly motivated postdoctoral Research Associate in research data science and analysis to join Professor Gerome Breen’s internationally recognised team at King’s
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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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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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. The successful candidate will work within a multidisciplinary team to unravel the metabolic drivers of HCC biology and transplant rejection through cutting-edge spatial multi-omics and computational metabolic
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‘Work, Welfare Reform and Mental Health’ programme. This involves collaborating closely with an interdisciplinary team of researchers as well as the Centre’s academic and community partners, as part of
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research programme takes a mixed methods approach. The successful applicant will have a key role in the qualitative work package which aims to understand multi-stakeholder perspectives of the C(E)TR process
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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