48 computational-physics-"https:"-"https:"-"https:"-"CEA-IBS" research jobs at King's College London
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King's College London, TPPC Physics Position ID: King's College London-TPPC Physics-TPPCSTFC26 [#31250] Position Title: Position Type: Postdoctoral Position Location: London, London, City of WC2R
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. Department: Res Dept of Biomedical Computing. Contact details:Dr Konrad Wagstyl. konrad.wagstyl@kcl.ac.uk Location: St Thomas Hospital. Category: Research. About Us The applicant will join the Wellcome
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THIS VACANCY IS OPEN TO INTERNAL CANDIDATES ONLY About Us We are seeking a highly motivated and experienced researcher to work on the large-scale programme and associated projects of the Data
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. Researchers benefit from state-of-the-art optics and prototyping facilities, high-performance computing for AI-driven analysis, and direct access to clinical environments. This multidisciplinary ecosystem
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professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across six
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, Biomedical Sciences, Biochemistry, Immunology, Microbiology, Molecular biology) to support a multidisciplinary research programme investigating various aspects of antiviral innate immunity. The successful
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises the Departments of Chemistry, Informatics, Mathematics, Physics. The Department of Mathematics has a
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neuroscience or developmental biology or equivalent Excellent skills in mRNA techniques, especially HCR labelling Confocal microscopy skills Computational experience, including coding Experience in using
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conferences in areas of machine learning, computer vision, and Large Language Models and high-impact specialist peer reviewed academic journals. • Ability to conduct interdisciplinary research activities
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, and with expertise in quantitative and qualitative methods, to develop a training and capacity-building programme and lead research projects working on large datasets. On training and capacity-building