650 machine-learning-and-image-processing-"RMIT-University" Fellowship positions in United Kingdom
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We are pleased to advertise three new posts providing an exciting opportunity to join the world-leading biomedical imaging research group at the Sir Peter Mansfield Imaging Centre (SPMIC
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Applications are invited for the role of Clinical Research Fellow in Imaging and Brain Cancer, based in the Magnetic Resonance and Precision Imaging (MR&PI) Theme of the Nottingham NIHR Biomedical
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translation of innovative miniature, hair-thin imaging devices we have previously developed (doi.org/10.1117/1.JBO.29.2.026002 ). These devices are designed to enable early and accurate detection of cancerous
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Applications are invited for the role of Clinical Research Fellow in Imaging and Brain Cancer, based in the Magnetic Resonance and Precision Imaging (MR&PI) Theme of the Nottingham NIHR Biomedical
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translation of innovative miniature, hair-thin imaging devices we have previously developed [https://doi.org/10.1117/1.JBO.29.2.026002]. These devices are designed to enable early and accurate detection
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months, in the first instance. Application Process If you would like to discuss this role please contact Prof Regent Lee at regent.lee@nds.ox.ac.uk Applications for this vacancy are to be made online. You
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developing machine learning or data science approaches for patient stratification and genetic association analyses using cardiac magnetic resonance imaging in biobank populations. Successful applicants will
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to contribute to an exciting European project developing hydrothermal processes for the management of solid digestate and other waste from the olive oil production process. About the Role We are seeking a
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individual and collaborative research in the area of Power Electronic, Machine and Control. The role holder will be expected to conduct and lead high-caliber, impactful research at the forefront of Power
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the Medical Research Council. The Research Fellow will be using Natural Language Processing (NLP) methods, with a special focus on generative Large Language Models (LLMs), to interrogate a very large sample of