124 computer-programmer-"https:"-"Inserm" "https:" "https:" "https:" "https:" "https:" "Dr" "P" Postdoctoral positions at University of Oxford
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of this position will be based in Oxford, with Dr Will Coulton, and the second 18 months at IPMU, with Dr Leander Thiele. Oxford hosts a large cosmology group with expertise in theoretical, observational, and
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research project lead by Oxford Materials (Professors Robert House (PI), Saiful Islam, Peter Bruce), with UCL Chemical Engineering (Dr Rhod Jervis) and 4 industrial partners that brings together expertise in
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Investigator (PI) Dr Finnian M. Moore Gerety, each post holder will be a member of the interdisciplinary research project Mantras in Religion, Media, and Society in Global Southern Asia (MANTRAMS), funded by a
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to their ongoing research programme, which aims to unravel the complex mechanisms underpinning 3-dimensional growth in plants. This is a fixed term position for one year. About you The successful applicant will hold
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We are seeking to appoint a Research Assistant in Brain Tumour Biology to join Dr Pathania’s Laboratory at Ludwig Institute for Cancer Research, part of Nuffield Department of Medicine. The lab
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We are seeking a talented and motivated postdoctoral researcher to join our Somatic Evolution Research group led by Dr Verena Körber . You will contribute in the research of somatic evolution during
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We are seeking a Senior Researcher to join a joint research programme between the Big Data Institute (BDI) in the Nuffield Department of Population Health and the Centre for Human Genetics in
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Applications are invited for a post-doctoral qualitative researcher, working with Dr Claire Friedemann Smith on three projects which aim to improve primary care cancer detection. One project focuses
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cutting-edge research at the intersection of Digital Sociology and Public Policy. The successful candidate will join a small but growing connected families research group led by Dr Ekaterina Hertog and Dr
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly