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and partner urban sites, the successful candidate will collect and analyse real-world environmental data to evaluate how vegetation interacts with the built environment. You will be supported by a
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There is growing UK and international interest in networked sensing and autonomous collaborative platforms, where multiple airborne sensors co-operate to collect and exploit data. In contrast
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on the study of the digital traces we left behind to capture human behaviour and social dynamics through the lens of Network Science, Complexity Theory, and Data Science. The team is made up of researchers in
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Research Assistant to investigate digital reading comprehension through large-scale data analysis. This role, funded by the John Fell Fund, sits at the fascinating intersection of computational
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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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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