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push the boundaries of neural scene representations in a medical imaging context. The successful candidate will work alongside a multidisciplinary team of deep learning researchers, computer vision
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(Python preferably) for medical imaging processing and machine learning. You are flexible, pro-active and an adaptable team worker. This is a full time, fixed term post (part time considered) for 12 months
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those with expertise in cardiac MRI acquisition. While experience in machine learning is not essential for this pathway, a strong technical understanding of imaging and post-processing is helpful. You
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The Oxford Applied and Theoretical Machine Learning group at the Department of Computer Science has a new opening for a Project Support Officer, working together with Professor Yarin Gal. In
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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated
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An exciting opportunity has arisen for a talented postdoctoral researcher to join the Oxford Machine Learning in Neuroimaging (OMNI) lab, led by Professor Ana Namburete, in collaboration with
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highly computer literate, with demonstrable experience in using common software applications e.g. MS Word, Excel, Outlook, Adobe Acrobat, and have the ability to learn quickly and use specialist software
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certification in data science, machine learning, or analytics, expertise in immunohistochemistry and digital imaging techniques. Previous experience working in a molecular or biochemistry laboratory and/or prior
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different modalities of microscopy (widefield, confocal, spinning disc, TIRF, super resolution), Image Processing (e.g., Fiji / ImageJ) and data analysis. • Good communication skills (written and oral
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exciting recent technological advances, having its impact on fields as diverse as medical imaging, conversational agents, astronomy, and many more. The Oxford Applied and Theoretical Machine Learning (OATML