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to the positive research culture of the Woolgar lab and the wider environment at the University of Cambridge. Interviews are expected to be held mid-December and the anticipated start date will be 01 February 2026
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of collaborative projects, working closely with clinicians, imaging experts, and computational scientists across the Oxford–Novartis Collaboration for AI in Medicine. You must hold a PhD/DPhil in Statistics
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, including engineers and veterinarians, to assess the effectiveness of the AG ARC machine. About you This position is ideally suited to a microbiologist with strong laboratory skills and an interest in applied
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related to staff position within a Research Infrastructure? No Offer Description About us The School of Cardiovascular and Metabolic Medicine & Sciences (SCMMS), is one of six schools in the Faculty of Life
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and progression. The position will require travel to University of Copenhagen to work closely with Dr. Julien Ochala, a leading expert in muscle biophysical assays. Travel and accommodation will be paid
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Research Associate to work with Professors Jon Keating and Louis-Pierre Arguin at the Mathematical Institute, University of Oxford. This is a 3-year, fixed-term position, funded by a research grant from the
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the Oxford–Novartis Collaboration for AI in Medicine. You must hold a PhD/DPhil in Statistics, Statistical Machine Learning, Deep Generative Modelling, or a closely related field, together with relevant
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functional genomic assays (methylome, transcriptome and proteome), generating and integrating multi-omic datasets to define how SkM contributes to ALS onset and progression. The position will require travel
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level postdoctoral research associate position. Working collaboratively, the associate will interview volunteers across worksites of pandemic relief communication, online vaccination, and digital
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Busani’s research group in the School of Mathematics at the University of Edinburgh. The position is funded by Dr Busani’s ERC Starting Grant “UnivKPZ” and offers the opportunity to contribute to cutting