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Field
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applicants from across the broad field of cognitive neuroscience with an imaging-informed programme that is complementary to our existing research portfolio. The successful candidate's cognitive neuroscience
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multilayer printed circuit boards (PCBs). It draws from disciplines including electrical and electronic engineering, embedded systems, computer vision, and cybersecurity. The ability to verify hardware without
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Additive Technologies) team at University of Warwick seeks a creative and motivated research fellow in the area of deep learning for (X-ray) image processing. The appointment is currently until 31 March 2027
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to explore include mono-chromatic and multi-chromatic illumination, structured illumination, and telecentric illumination distortions. Computer based image analysis approaches will be developed, including
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for Computational Psychiatry and Ageing Research. We are now recruiting an internationally recognised leader in the field of imaging-informed cognitive neuroscience to work with some of the world’s leading
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technologist to join our PET imaging team at King’s College London (KCL) & Guy’s and St Thomas’ (GSTT) PET Centre. The Centre is part of both King's College London's School of Biomedical Engineering & Imaging
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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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both King's College London's School of Biomedical Engineering & Imaging Sciences (BMEIS) in the Faculty of Life Sciences and Medicine, and Guy's & St Thomas' National Health Service (NHS) Foundation
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embedded in the School of Biomedical Engineering & Imaging Sciences, a vibrant community of engineering designing and translating technology into the clinical. The project will follow the King’s College
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related field* Experience with multi-modal medical image registration Computer programming skills (e.g., Matlab, Python, C++) Strong academic record, evidenced by publications in peer-reviewed journals and