31 computer-science-image-processing positions at University of Oxford in United Kingdom
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analysis, and may contribute to scientific publications. The CRF will work closely with the broader multidisciplinary team, including postdoctoral researchers in biomedical engineering and computer vision
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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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medical image analysis and natural language processing, with applications in cardiology within a global context. You will be responsible for the design and testing of bespoke AI models for cardiac imaging
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Master’s degree in physics, mathematical biology, computational biology or a related subject. They should have good skills in programming languages such as Python, MATLAB or R, and experience in image
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must hold a Masters or PhD in a relevant field such as cardiac imaging, biomedical engineering, computer science, Physics, or a related discipline. Prior experience in MRI research, including working
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processes at the molecular, cellular, tissue and systems level of organisation. In so doing we provide a bridge to translational medicine, and interface between physical and life sciences. We are committed
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processes at the molecular, cellular, tissue and systems level of organisation. In so doing we provide a bridge to translational medicine, and interface between physical and life sciences. We are committed
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term until 30 September 2026 About us: At the Department of Physiology Anatomy & Genetics (DPAG) we undertake discovery science where we reassemble physiological processes at the molecular, cellular
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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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Leedham (colorectal cancer biology), Dan Woodcock (cancer genomics), Helen Byrne (mathematical modelling), and Jens Rittscher (computational pathology and imaging AI), offering a unique opportunity to work