617 proof-checking-postdoc-computer-science-logic Postdoctoral research jobs in United Kingdom
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52 Faculty of Chemistry Startdate: 01.10.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 30.09.2028 Reference no.: 4486 Explore and teach
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About the role We are seeking a full-time Postdoctoral Researcher to join the Oxford Secure and Advanced Computer Architecture Research (OSCAR) group at the Department of Engineering Science
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partners and will innovate new mechanisms to secure future computing systems at lower costs and performance overheads. About you You should possess a PhD/DPhil in Engineering, Computer Science or other
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support a high-value materials characterisation programme as a postdoctoral researcher. The ability to think outside the box with creativity, along with having the drive and ambition to develop those ideas
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experience in stem cell biology. You should have an extensive hands-on experience in culturing human iPSCs and iPSC-derived cellular models as well as experience with molecular cloning and generating knockout
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group investigates RNA biology in the context of blood vessel formation, with the aim of uncovering new mechanisms that regulate endothelial cell function and angiogenesis. The successful candidate will
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between Departments is important to the role which will be based in the Materials Innovation Factory. The post will involve leading an iterative programme of applied polymer chemistry and materials science
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, computational biology, and haematological cancer? We have an exciting opportunity for a Senior Postdoctoral Researcher to be a part of a collaborative interdisciplinary initiative at the Ludwig Institute
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27 Aug 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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Nuffield Department of Clinical Neurosciences (NDCN), MRC Brain Network Dynamics Unit, Mansfield Road, Oxford The post holder will develop computational models of learning processes in cortical