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Research theme: Nuclear thermal-hydraulics How many applications: 1 How to apply:uom.link/pgr-apply-2425 This project is co-funded by EDF R&D UK and the University of Manchester. Funding covers
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research team. Good knowledge and experience in heat and mass transfer is essential and proficiency in the use of Computational Fluid Dynamics will be considered an advantage. The student will benefit from
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studies in the Julia programming language. The successful candidate should have a strong mathematical background, particularly in dynamical systems theory, and a keen interest in network science, and
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and deterministic AI outputs is critical. This requires robust design principles and architectural changes to reduce variability and integrate smoothly with industrial control systems. Enhancing
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, curious individual to join an exciting PhD. This opportunity is generously funded by John Crane Ltd, a world-renowned engineering technology leader. Why This PhD? Impact Clean Energy's Future: Develop next
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to rural and coastal health research. With £10.9m of funding from Research England, this innovative centre is striving to understand the intersection between place-based deprivation and poorer outcomes
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should have a strong mathematical background, particularly in dynamical systems theory, and a keen interest in network science, and scientific computation. The student will gain invaluable experience
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efficiency than conventional materials. This research is highly interdisciplinary, so we invite applications from candidates across all relevant areas, including but not limited to: Chemistry
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Current modelling and simulations require either generic assumptions to be made for fluid dynamic based modelling leading to inaccuracies between modelled and experimental data or, intense
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load emulation, surface tribology and lubricants, contact mechanics or dynamical phenomena. This is an opportunity to work within a world-class multidisciplinary team within the Engineering Systems