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About us Our Big Data in Health team at the University of Southampton is based in the Primary Care Research Centre. We are an interdisciplinary group conducting innovative research to address
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responsibility for: Designing, implementing, and overseeing large-scale team projects, including multi-year projects, in collaboration with Analysis and Data teams to ensure projects support CSET's data-driven
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of gender, political communication and “everyday sexism” Analysing and interpreting research findings and results based on large scale media data sets Contributing to engagement with non-academic partners, co
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the use of large administrative data to understand and address inequality. OI has published seminal work on national trends in upward mobility ; racial disparities ; the role of neighborhoods , social
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. The project, "Building the bridge from GWAS to Breeder through multi-omic network data fusion", focuses on transforming GWAS discoveries into actionable breeding insights. Using sorghum as a model, the work
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expertise in life cycle assessment, soil science, and big data analytics. This role offers you the chance to directly impact global food security and environmental sustainability while working in a
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internationally recognized leader in the science of economic mobility and in the use of large administrative data to understand and address inequality. OI has published seminal work on national trends in upward
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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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. 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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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