535 postdoc-computational-fluid-dynamics-"Prof" Postdoctoral positions in United Kingdom
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seconded to national and international organisations, helping to shape policy and practice nationally and internationally. About the role We are seeking two dynamic researchers interested in working as part
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BBSRC grant awarded to Prof Francesco Licausi. The work is to be conducted in the Life and Mind Building, Department of Biology, University of Oxford. The postholder will work on the molecular mechanisms
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52 Faculty of Chemistry Startdate: 16.06.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 15.06.2028 Reference no.: 4101 More than 7,500
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. The QSL currently comprises approximately 50 core members, under the leadership of Prof. Elham Kashefi, Personal Chair in Quantum Computing and the Chief Scientist at the NQCC. The Opportunity: These posts
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Assistant (Postdoc) to join the research team led by Univ. Prof. Olga Mula. Our group’s work sits at the forefront of numerical analysis for Partial Differential Equations, enriched with data-driven
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data models for electronic health records of people with mental disorders, under the guidance of Dr Osimo and Prof Murray at Cambridge, and a line manager to be selected at Akrivia Health. The aim
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of Liverpool. The successful applicant will work primarily with the UK PI Dr Richard Brown (Durham) and Co-I Prof Paul Brennan (UCL), Co-I Prof Patrice Carbonneau (Durham), and Co-I Dr Silvio de Angelis, and
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duration of ten months (10 months), and is full-time. Reporting to Prof. Gesine Reinert, the post holder will be a member of a research group with responsibility for carrying out research in the area of
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explores novel aggregation methods at the intersection of AI safety, computational social choice, and judgment aggregation, aiming to formally integrate multi-stakeholder preferences into AI system design
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their dynamics. This will be carried out on a highly noisy incomplete data, posing a significant theoretical and computational challenge. Validate the developed methods in simulations and in real neuronal