35 postdoctoral-image-processing-in-computer-science Postdoctoral positions in United Kingdom
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processing in the mammalian cochlea in vivo , and how these influence central auditory neuronal pathways. The project will primarily involve using in vivo 2-photon imaging and AAV-gene delivery applied to a
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departments: Cardiovascular Imaging, Cancer Imaging, Early Life Imaging, Imaging Chemistry & Biology, Biomedical Computing, Surgical & Interventional Engineering, Imaging Physics & Engineering and Digital Twins
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solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated and real clinical scenarios. Evaluation may involve quantitative studies
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departments: Cardiovascular Imaging, Cancer Imaging, Early Life Imaging, Imaging Chemistry & Biology, Biomedical Computing, Surgical & Interventional Engineering, Imaging Physics & Engineering and Digital Twins
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Postdoctoral Researcher to join Dr Andrada Ianus at the School of Biomedical Engineering & Imaging Sciences, King’s College London, working in close collaboration with Dr. Po-Wah So at the Institute
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experimental and computational approaches are employed to shine light into key biological processes during the life of parasitic flatworms. Large-scale sequencing datasets (‘omics’) are generated and analyzed
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An exciting new opportunity for a Postdoctoral Research Associate has become available within the Bivalve Transmissible Neoplasia Group (www.zoo.cam.ac.uk/btn ), a newly-established small
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Postdoctoral Researcher to join Dr Andrada Ianus at the School of Biomedical Engineering & Imaging Sciences, King’s College London, working in close collaboration with Dr. Po-Wah So at the Institute
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collaboration with the Translational Gastroenterology Unit (TGU) and the Ludwig Institute of Cancer Research (LICR) we aim to develop a computer guided endoscopy image recognition system that will support
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collaboration with the Translational Gastroenterology Unit (TGU) and the Ludwig Institute of Cancer Research (LICR) we aim to develop a computer guided endoscopy image recognition system that will support