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Field
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model predictive control (MPC) methods to enable large groups of buildings to dynamically form coalitions and provide flexible energy services. Your work will incorporate advanced robust MPC techniques
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treatment and improved clinical outcomes. The supervisory team of Dr. Paul Facey, Dr. Claire Morgan and Prof. Dean Harris, bringing expertise in cancer genomics, microbiology, and clinical translation
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Establishment). Recent work by the group (leading to REF 4* rated outputs and several Keynotes) has contributed to bridging the gap between Computational Solid and Fluid Dynamics, with a unified computational
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model of high-pressure mechanical seals. Apply Computational Fluid Dynamics (CFD): Simulate gas film flow within the microscopic seal gap. Couple CFD with Structural Models: Study the fluid-structure
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position initially and is expected to be held full time and in person. You will join the CNNP Lab, which is well supported with recent funding of over £3M. The lab is based in the School of Computing
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, dynamical systems and statistical physics. The candidate will be jointly supervised by the Coventry team Dr Fei He and the Stellenbosch team Prof. Francesco Petruccione . This project will contribute
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variants of importance sampling. We will connect these methods to modern formulations of Monte Carlo algorithms to improve their accuracy, scalability, and overall computational cost. The methodology so
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explore the nonlinear structural dynamics of LGSs to fully understand the complexity of their control. They will use this foundation to explore idealised and realistic control laws to virtually “stiffen
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the field of Computational Morphodynamics in plants. The work will be within the ERC-funded project RESYDE (https://resydeproject.org ) with the aim of building a virtual flower using multi-level data and
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spoken communication skills The following skills are desirable but not essential: Demonstration of undertaking research projects Ability to program Previous experimental experience in fluid dynamics