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conduct in vivo experiments to investigate retinal neurovascular dynamics using the AO-RSO system; Develop or adapt high-speed image acquisition and processing methods for simultaneous measurement
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departments: Cardiovascular Imaging, Cancer Imaging, Early Life Imaging, Imaging Chemistry & Biology, Biomedical Computing, Surgical & Interventional Engineering, Imaging Physics & Engineering and Digital Twins
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departments: Cardiovascular Imaging, Cancer Imaging, Early Life Imaging, Imaging Chemistry & Biology, Biomedical Computing, Surgical & Interventional Engineering, Imaging Physics & Engineering and Digital Twins
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’ Hospital in central London in the School of Biomedical Engineering & Imaging Sciences at King’s College London: https://www.kcl.ac.uk/bmeis . There is an unmatched infrastructure in place to support the
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assigned Requirements A Ph.D. degree in Neuroimaging, Biomedical Engineering, Electrical Engineering, Physics, Computer Science, or other related disciplines, with experience or keen interest in processing
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’ Hospital in central London in the School of Biomedical Engineering & Imaging Sciences at King’s College London: https://www.kcl.ac.uk/bmeis . There is an unmatched infrastructure in place to support the
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resonance imaging) Fluency in English Experience and knowledge: Required: Experience in computer programming Expertise in Python programming for Machine and Deep Learning, e.g., sklearn, pytorch, tensorflow
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science, and computational imaging. • Access to state-of-the-art HSI and spectroscopic instrumentation (HySpex VNIR/SWIR systems, Macro-XRF, Raman, FTIR, etc.). • Active participation in international in
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signal/image processing, computer science, applied mathematics, or a related field, obtained less than 3 years before the date of hire. Essential skills, knowledge and experience: Excellent command
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to the development of the research milieu. Requirements PhD degree in a field closely related to the position (e.g., computerized image analysis/processing, machine learning, artificial intelligence, data science