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Field
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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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an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine learning techniques and experience with coding in Python is beneficial (but not a strong requirement
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environments. · Expertise in computer literacy, MS Office packages and electronic databases. · Proven excellence in handling and entering data including an understanding of data protection and confidentiality
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of neural activity will be used in conjunction with advanced imaging methods and behavioural assays to investigate how signals beginning in the retina and transmitted through different visual pathways
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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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Criteria Master’s degree (or equivalent experience) in Machine Learning, Computer Science, Medical Imaging, Biomedical Engineering, or a related field. Experience with deep learning frameworks (e.g
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methods, signal processing techniques, and comparison with alternative detection technologies. ii. Support design and development of NQR prototype, including system architecture, component selection, and
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researchers from within the School of Biomedical Engineering & Imaging Sciences, the wider Trust and University and across the UK and internationally. About The Role We are looking for an exceptional lecturer
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22 Aug 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Educational sciences Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country
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collection activities. Supervision will be provided by academics from various disciplines specializing in biomechanics, image processing, and computer vision, alongside orthopaedic surgeons and academics.