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TypeFixed-termWorking TypeHybridAvailable for SecondmentNoClosing Date30-Apr-2026JD_Param11NoJD_Param12No Two 3.5 year PhD studentships in Artificial Intelligence in Medicine, or Health Data Science, funded
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group, including PhD and MSc and honours project students. You will also be heavily involved with data analysis and writing up manuscripts. Please see the below 'Job Description' for further details
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‑bounded turbulence. This short, intensive 9‑month position offers an exciting opportunity to advance fundamental turbulence research using DNS/LES and data-driven optimisation techniques. In this role, you
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as a mechanism to ensure transparency, accountability, and resource efficiency throughout the battery value chain. These passports store and share verifiable information on a product’s origin
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useful information beyond established clinical risk scores. Phase 2: Linking clinical status to atrial electrical remodelling (n ~100): In a clinical ablation cohort, we will relate standard procedural
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with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from
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Data is more valuable than oil, so it has been said. Quantum computing offers new unusual datasets thereby presenting new opportunities for AI approaches. Quantum computing is raising the prospect
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Studentship Information Supervisor: Professor Ian Fisk Secondary Supervisor: Dr Vincenzo di Bari, Dr Louise Hewson, Mui Lim Subject Area: Food Science Research Title: Sodium Reduction in Coated
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the network, and every synapse is updated, on every epoch. Recent work has begun to challenge both halves of this independently. Progressive Data Dropout has shown that progressively reducing the training set
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resolution. This PhD offers the opportunity to conduct cutting-edge research with direct industrial impact, combining fundamental fluid mechanics with modern data-driven techniques. The successful candidate