133 postdoc-computational-biomedical-engineering Postdoctoral positions at University of Oxford in United Kingdom
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projects. It is essential that you hold a PhD/DPhil in a quantitative or computer science related subject (e.g. Statistics, Machine Learning, Biostatistics, AI, Engineering), and have post-qualification
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source of information and advice to other members of the group on scientific protocols and experimental techniques. You will hold a PhD/DPhil (or near completion) in a biomedical discipline with direct
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applications. In this role, you will take the lead on an independent project within our broader research programme. Your work will centre on identifying and characterising novel regulators of the immune response
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vitro and cell-based approaches. In this endeavour the position is for a Postdoc with expertise in cell signalling pathways, protein biochemistry and in vitro cell biology. You will be responsible
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these bioinformatic experiments. Access to a high-performance computer will be provided. The candidate must be capable of generating complex molecular compound models in silico and using current molecular dynamic
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until 30 March 2026, and may be extended subject to the availability and renewal of external funding. With a background in materials science, materials processing or related engineering or physical
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candidate will hold a PhD in physics, biophysics, physical chemistry, engineering, or a related area, or have submitted a PhD thesis prior to taking up the appointment. The research requires strong interest
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in the Department of Chemistry, University of Oxford, for a period of up to 3 years. The project involves the development of methods to use light to regulate transport of amino acids and to engineer
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The Oxford Internet Institute has an exciting opportunity to join the Governance of Emerging Technologies research programme, working under the supervision of Professor Brent Mittelstadt and
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hepatitis and liver disease. This post is funded by the National Institute for Health and Care Research (NIHR) as part of a significant research programme that leverages large-scale healthcare datasets