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Field
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Imaging of Materials Facility (AIM ) led by Professor Richard Johnston and Swansea University's Simulation and Immersive Learning Centre (SUSIM ). The student will develop novel medically bespoke protocols
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This project aims to enhance best practices in strain quantification for biomedical applications, facilitating the transition of image-based measurement methods from laboratory research to clinical
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Centrum Wiskunde & Informatica (CWI) has a vacancy in the Computational Imaging research group for a talented PhD student (m/f/x), on the subject of: Fast and low-dose medical imaging using multi
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journals. Close collaboration with team members and colleagues. Essential qualifications: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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annotations are scarce or unreliable. Recently developed unsupervised learning methods allow to circumvent this limitation by learning patterns in unlabelled medical images and then leveraging them
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for biology and healthcare; then, the Chair of Biological Imaging (CBI) at the Technical University of Munich (TUM), and its integrated Institute of Biological and Medical Imaging (IBMI) at the Helmholtz
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Roentgen’s Nobel Prize-winning discovery of X-rays enabled us to non-destructively image inside the body, birthing medical diagnostic imaging and revolutionising materials characterisation
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the Neurocritical care unit and austere environments including space flight. The current project will require the candidate to obtain several ultrasound images, measure, and categorize them with opportunities to be
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the Neurocritical care unit and austere environments including space flight. The current project will require the candidate to obtain several ultrasound images, measure, and categorize them with opportunities to be