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project funded by the Leverhulme Trust. Description below: The density of information content in screen media – i.e., the light, volume and pitch changes from which we extract meaning – has increased
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Closing Date Sunday 17 August 2025 Reference PHD002-25 A funded PhD position is available on a project funded by the Leverhulme Trust. Description below: The density of information content in screen media
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A funded PhD position is available on a project funded by the Leverhulme Trust. Description below: The density of information content in screen media – i.e., the light, volume and pitch changes from
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myriad of new techniques and much sought-after skills demanded by industry, including the following: Design of experiments, data harvesting/analysis and interpretation of results to derive insight
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complex input. For instance, in physics-informed ML, in addition to data examples used by a standard ML setup, domain knowledge serves as an additional input. It can be in an explicit form of rigorous
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Grand Tours, one-day races (monuments and semi-classics), and select World Tour 1-week stage races. The data sources will include video and previous race commentary to ‘code’ key events in races that help
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population-based studies. Using data from 11 million vessel segments from over 200,000 CFPs, we have shown that retinal vasculometry can predict cardiovascular disease as well as established risk scores and
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methods for defect detection; Apply AI and machine learning techniques to process, analyze, and interpret complex NDE data; Create AI models for automated defect detection, classification, and
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are eligible to apply. The successful candidate will receive a tax free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. The start date is 1st October 2025. Visualising data
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studentship, commencing in October 2025 as part of the second EnerHy intake, is based at the University of Strathclyde and centres on advanced analytics for wind energy data. Research Project Overview The wind