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Field
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the field, from tissue scaffold design in tissue engineering evaluation to surgery. The student will focus on establishing best practice for widespread applicability, building on past skin, heart, lung, brain
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background in biology, programming or mathematics is meritorious. Knowledge in medical image processing, image registration, and large-scale analyses of genetic (including Mendelian randomization), protein, or
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At the Faculty of Engineering and Science, Department of Materials and Production a position as PhD stipend in Muscle Neuromechanics and Ultrasound Imaging, within the doctoral programme Materials
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(or equivalent) in an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject area: Medical imaging, biomedical engineering, computer science & IT
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evolutionarily recent genes may buffer or exacerbate these effects. About the Labs The Bonin Lab investigates cortical circuit function in sensory systems using in vivo imaging and computational modeling
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evolutionarily recent genes may buffer or exacerbate these effects. About the Labs The Bonin Lab investigates cortical circuit function in sensory systems using in vivo imaging and computational modeling
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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orbital parameter extraction using image processing techniques. The ideal candidate should have a strong background in physics, engineering or a related field, as well as experience working with programming
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) publication at top tier ranked international conferences and journals in Computer Science. Person specification: MSc in Computer Science or AI (minimum of 2:1 degree or higher) UK home student status holder
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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer