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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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Systems, or a related field. Strong analytical and critical thinking skills. Strong machine learning (ML), computer vision (CV), large language models (LLM) for quantitative data, texts, images, and sensor
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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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scientist to lead the analysis and interpretation of multimodal imaging, including spatial transcriptomics, single cell and large-scale omics data, digital pathology, using cutting-edge AI and machine
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine
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–200) desirable, as well as experience in TEM/STEM image processing and simulation using open-source Python packages such as atomic simulation environment (ASE) and abTEM. A willingness to occasionally
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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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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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research program that takes advantage of the Total Body PET scanners and other PET Centre facilities in tandem with building collaborations with the Research Department of Imaging Chemistry & Biology working