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this technology and create stand-alone units within washroom and cleanrooms. We will develop widefield fluorescent imaging techniques to segment contamination from instruments, with automated multi-spectral overlay
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to the clinic The post holder will be based in the Department of Biomedical Computing as part of the School of Biomedical Engineering & Imaging Sciences, King’s College London, a vibrant community of engineers
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treatments. To achieve this, we will develop personalised cardiac models at scale, and update these models over time, using imaging and electrical data collected by collaborators at multiple centres. We
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treatments. To achieve this, we will develop personalised cardiac models at scale, and update these models over time, using imaging and electrical data collected by collaborators at multiple centres. We
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of Biomedical Computing as part of the School of Biomedical Engineering & Imaging Sciences, King’s College London, a vibrant community of engineers designing and translating technology into the clinical
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to the clinic The post holder will be based in the Department of Biomedical Computing as part of the School of Biomedical Engineering & Imaging Sciences, King’s College London, a vibrant community of engineers
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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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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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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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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