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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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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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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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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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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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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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of Singapore's research and innovation ecosystem and aims to support the development of a sustainable, climate-resilient, and healthy city through data-driven design and policy-relevant research. The programme
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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
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to think analytically and creatively. Good computer skills, plus good presentation and writing skills in English, are required. Previous research experience in contributing to a collaborative