216 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" positions at King's College London
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epilepsy using very large EHR datasets. Real world data in EHRs includes extensive and rich detail about the presentation, phenotype, investigations, diagnosis, comorbidities, treatments, encounters with
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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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. 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 human health. Based at King’s St Thomas’ campus, we manage the TwinsUK cohort which was established in 1992. We now have data on more than 16,000 identical and non-identical twins, making TwinsUK the UK’s
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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
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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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ensure that all courses are scheduled efficiently to meet business needs and that attendees are booked and reminded to attend. You will be able to produce data and metrics to support the training that has
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members in data analysis best practice and accurate record keeping and will be encouraged to present at international meetings and publish in high-impact journals. A major component of the position will be
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, clinically validate, and prospectively evaluate, a novel in-silico tool that uses patient imaging data to reconstruct personalised ‘digital twin’ cardiac models to provide pre-procedural ablation target