597 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" scholarships in United Kingdom
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opportunity. Please contact Mary Ivers, Interim Associate Director, External Engagement at m.b.ivers@greenwich.ac.uk for more information. Eligibility Criteria Priority for the scholarships will be given
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are typically superior to self-report measures in terms of data accuracy and resolution. For this reason, wearables are being used increasingly in physical activity–related research, but their use in
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epidemiology. We are keen for this PhD project to be student-led and shaped and driven by the successful candidate’s research interests and skills. Techniques to be used: Epidemiology Statistics and data
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the challenge of forever chemicals in drinking water. The aim of this research is to develop a smart data predictive model that will support utilities’ evidence-based decision-making to improve the resilience and
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electrical engineering and data science. The role is for the third intake of the EnerHy programme which commences in October 2026. Research project overview: This role offers an exceptional opportunity for a
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mechanistic, dietary and clinical analyses embedded within a double‑blind randomised controlled trial of tirzepatide. Project Description You will analyse Intake24 dietary recall data collected during the trial
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tradeable points can be used under the rules. Information on other visa options is available at www.gov.uk/check-uk-visa . Please do not hesitate to contact Grant Rae, HR Adviser (e-mail: grant.rae@abdn.ac.uk
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TypeFixed-termWorking TypeHybridAvailable for SecondmentNoClosing Date30-Apr-2026JD_Param11NoJD_Param12No Two NIHR UCL UCLH BRC Studentships in Artificial Intelligence in Medicine or Health Data Science Two
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Project advert This PhD will pioneer the first species-level monitoring framework using drone-based multispectral data fused with very-high-resolution satellite imagery (Pleiades Neo), powered by
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trigger redesigns across multiple groups. The challenge is compounded by the fact that each discipline uses different data models and representations, making system-level interdependencies difficult