240 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UNIV" 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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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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an exciting opportunity for a Postdoctoral Research Associate to join their dynamic, interdisciplinary team to shape how multimodal bioimaging data is stored, shared and reused. The Parsons Group is based in
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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