45 image-coding-"EPIC" Postdoctoral positions at University of Oxford in United Kingdom
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We are seeking a full-time Postdoctoral Research Assistant in “Resilient Temperature- and Pressure-Sensitive Paints for Hyperspectral Imaging” to join Prof. Jin-Chong Tan’s group (Multifunctional
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We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image
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crystalline resins for use in two-photon polymerization. New forms of imaging hardware will be utilized in collaboration with partners to provide greater understanding of the polymer network morphology and how
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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
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and temperature on overall mechanical response, and will have the opportunity to field high-speed imaging, digital image correlation, laser velocimetry, and related techniques to enhance the type and
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imaging, digital image correlation, laser velocimetry, and related techniques to enhance the type and level of detail extracted from these experiments. As part of this role, you will work closely with other
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The University of Oxford is seeking a highly motivated Postdoctoral Scientist with expertise in biostatistics, machine learning, and cardiac magnetic resonance imaging (MRI) to join Professor Betty
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-on experience in at least one of single-cell or spatial omics, imaging, or other high-dimensional biological data types. You interrogate existing literature critically, design rigorous experiments and deliver
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spatially-resolved models of metastatic outgrowth in the liver which account for interactions between stromal, immune and tumour cells. You will analyse quantitative imaging data from a variety of sources
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics