169 post-doc-image-engineering-computer-vision Postdoctoral research jobs at University of Oxford in United Kingdom
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Applications are invited for a Postdoctoral Research Assistant in Ion Trap Quantum Computing. The post is available initially for a fixed-term duration of 3 years, with the possibility of extension
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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measuring a molecule’s size and shape in the solution phase (Science 2025). Our microchip-based escape-time technology platform now enables measurements of the physical properties of macromolecules such as
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Are you passionate about taking a lead role in a cutting-edge project at the intersection of genomics, computational biology, and haematological cancer? We have an exciting opportunity for a Senior
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biophysics, and cutting-edge analytical technologies. Your expertise in optical microscopy, single molecule imaging, computational imaging and data analysis will help us further develop mass photometry and
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research programme at Oxford. Candidates should hold a PhD in biomedical engineering, computer science, medical physics, statistics, or a related field. A strong track record of first-/senior or co-author
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the AM fungus, R. irregularis. The project focuses on obtaining a mechanistic understanding of EV biogenesis, cargo loading and signals that regulate EV release during the interaction. The post-doc will
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that regulate EV release during the interaction. The post-doc will work closely with lab members but with a focus on EV-associated fungal proteins. They will assist in protocol and technique development and use
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We are seeking a full-time Postdoctoral Research Assistant to join Torr Vision Group at the Department of Engineering Science, central Oxford. The post is funded by EPSRC and is fixed-term
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Colorectal Cancer - Stratification of Therapies through Adaptive Responses (CRC-STARS) programme, developing and applying cutting-edge mathematical methods to spatial transcriptomics imaging data in order to