242 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at King's College London
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| King's College London ). The research in Photonics & Nanotechnology Group ( https://www.kcl.ac.uk/research/photonics-nanotechnology ) involves the development and applications of advanced photonic
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the increasing demand for advanced statistical expertise in clinical trials, including first-in-human studies, trials involving digital health technologies, real-world data analyses, and translational research
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on U.S.-China relations, BA module on contemporary strategy in East Asia, and MA module on East Asian security. They will also be expected to contribute to leadership in teaching through module convening
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data in EHRs includes extensive and rich detail about the presentation, phenotype, investigations, diagnosis, comorbidities, treatments, encounters with hospital services, and clinical outcomes for very
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, including first-in-human studies, trials involving digital health technologies, real-world data analyses, and translational research. The post holder works as part of a team, with day-to-day responsibility
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, informatics, and data science as applied to both mental health and general medicine research. We have significant national and international collaborations, and our research has growing impact into all areas
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. The post is offered at a competitive salary (Grade 6, Spine Point 33 on the KCL salary scale), and includes provisions for travel money, computer equipment and academic and leadership training. This is a
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conditions. About the role: We are seeking a highly motivated postdoctoral Research Fellow in statistical genetics and genomic data science to join Professor Gerome Breen’s team at King’s College London and
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. This role is based within the Faculty of Life Sciences and Medicine, in the Department of Infectious Diseases, which brings together expertise across microbiology, immunology, clinical sciences, data science
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’ to ablate. Here, we aim to further develop, clinically validate, and prospectively evaluate, a novel in-silico tool that uses patient imaging data to reconstruct personalised ‘digital twin’ cardiac models