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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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assessments in these studies involved large, high quality, multi-informant and multi-method assessment batteries including diagnostic interviews, direct observation tasks, health economics data and a large
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business, Improving health & public services organisation, Strengthening economic & financial systems as well as our overarching themes AI, Digitalisation, Big data and Automation. King's expects all
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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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complementary. Broadly the posts include a qualitative research methods expert, a qualitative research methods expert in big data, and a quantitative research methods expert. Please note that this post may be
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digital infrastructure and transport infrastructure, and the need to provide standard services, including emergency responses, across large geographical areas. The aims of the CARMHRS study are: To improve
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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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of large multidimensional real world data sets using Stata, R, Python, or similar. Knowledge of C++ would be advantageous but not essential. Ability to communicate complex information clearly. Excellent
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will be complementary. Broadly the posts include a qualitative research methods expert, a qualitative research methods expert in big data, and a quantitative research methods expert. Please note that
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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