564 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Washington University in St" PhD positions in United Kingdom
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tasks involve the detection, discrimination, and interpretation of coloured signal lights and information presented on modern digital cab displays. The project will combine visual task analysis, spectral
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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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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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in porous geological formations. The successful candidate will develop and implement computational models, validate them against experimental or field data where available, and contribute to the design
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data analysis pipelines using ImageJ, R, MATLAB and relevant programming languages. Plan, troubleshoot and optimise experiments, maintain meticulous records, and prepare data, manuscripts and grant
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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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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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representatives. The post-holder will have access to a range of data resources to inform the model, including blood donor cohorts from the COMPARE, INTERVAL and STRIDES studies. It is anticipated the work will
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level, with sub-metre precision? This PhD will develop next-generation foundation-model-driven urban perception systems that fuse: high-resolution satellite imagery, aerial data, street-level imagery (e.g