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). The project investigates how machine learning (ML) can be used to enhance the modelling of boundary layers in industrial CFD simulations, where complex geometries and computational constraints limit near-wall
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harmonisation, and next generation research infrastructures. You will contribute to research projects enabling secure, interoperable, and scalable AI-driven use of clinical data for complex diseases such as
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Institute of Physics that focuses on complex fluids and soft mesoscopic materials, both experimentally and computationally. There are strong links with soft condensed‑matter theory and computational chemistry
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of length scales from small molecular units to long chained polymers, with even simple substances such as nitrogen or methane exhibiting complex phase behaviour. Methods to map this behaviour are well
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About the project: Advanced Monte Carlo methods for glassy dynamics and complex materials Supervisor: Dr Michael Faulkner, University of Warwick Glasses are materials that combine macroscopic solid
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PhD Position in Sequential Decision-Making Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application deadline: 15 May 2026
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PhD position in AI and Human Centered Decision Making Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application deadline: 5
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chemistry Computer science » Programming Computer science » Modelling tools Neurosciences » Neurobiology Neurosciences » Neurology Neurosciences » Neurochemistry Pharmacological sciences » Clinical
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Location: The University of Auckland
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the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The research will