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. The project will define new near miss and severe morbidity definitions allowing us to identify electronically when significant events happen. We will then develop a large multi-centre maternity routine dataset
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to modern slavery in conflict settings. This attempt requires a large, interdisciplinary team working within a cross-cutting framework to connect vast amounts of data and answer many fundamental questions
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electronically when significant events happen. We will then develop a large multi-centre maternity routine dataset for the first time. This will allow us to work out the best vital-sign-based early warning score
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techniques to enable large-scale data search across Personal Online Datastores (pods) hosted on distributed pod servers, addressing both keyword-based search and SPARQL querying. EPRESSO will build on and
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apply the Helsinki Discrete Element Model (HiDEM) to simulations of brittle-elastic fracture, calving and retreat at Kangerlussuaq Gletsjer (KG), a large outlet glacier of the Greenland Ice Sheet. Working
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to modern slavery in conflict settings. This attempt requires a large, interdisciplinary team working within a cross-cutting framework to connect vast amounts of data and answer many fundamental questions
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clinical trial portfolio for a research programme in antimicrobial resistance and work to support colleagues in data-enabled trials. You will also undertake statistical methods research associated with
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observation tasks, health economics data and a large battery of questionnaires. Because of the quality of the datasets, the elevated risk of children involved and the importance of the research questions, we
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Research Fellow in Intervention Development to join the Big Data in Health Group About us Our big data in health team at the University of Southampton is based in the Primary Care Research Centre
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will develop, implement, and apply advanced computational tools and reproducible workflows to interrogate large-scale, liquid chromatography–mass spectrometry (LC–MS)-based comparative metabolomics