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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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outputs across Projects 3-1 and 3-2 Manage and process large sets of operational data for case study analysis Contribute expertise in power grid optimisation to enhance planning models Participate in
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interdisciplinary team at the Technische Universität Dresden, focusing on the integration of multi-omics data to better understand, diagnose, and treat metabolic diseases (i.e. obesity, diabetes, metabolic
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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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quantitative data analysis of large secondary datasets and be based at the University of Bristol. There are opportunities to work on several other ongoing and upcoming research projects to help develop your
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will include leading and undertaking quantitative data analyses, including working with large-scale longitudinal survey and administration data, to generate novel insights and contribute to high-quality
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-resolution spatial transcriptomics and multiplex imaging, to turn large-scale data into actionable insights for both fundamental and translational research. About the role We are seeking a Senior
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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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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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using large language models, disease endpoint coding initiatives, and creation of common data model (CDM). He/she will also be expected to support/lead high-quality research in chronic disease