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phenomena. The project will contribute to numerical method development as well as new understanding of flow physics and will make use of high performance computing (HPC) and advanced computational fluid
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Overview This post is funded by the Quantum Computing Hub (QCI3) supported by the Engineering and Physical Sciences Research Council (EPSRC). The QCi3 Hub is part of Phase III of the UK’s Quantum
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Simulation of particle physics experiments on graphical processing units School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof D Costanzo Application Deadline
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for classical imagery inspections (e.g. CCTV) in sewer pipes treated with CIPP lining employing powerful semi-analytical and hybrid (numerical+analytical) acoustic simulations. During the project lifetime
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. Working closely with the academic Research Area Leads, the Research and Business Engagement (RBE) Lead will have direct responsibility for leading business engagement activities for Modelling and Simulation
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characterisation equipment at the University of Sheffield. There may also be opportunities to learn and apply computational methods such as process simulation using Population Balance Modelling, DEM simulations and
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simulation framework for the solar atmosphere. SAMS is being designed to incorporate world-leading physics capabilities and enable time-dependent, non-LTE radiative transfer magnetohydrodynamic (MHD
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). Modelling tools used will vary according to application but are likely to including process simulation using Population Balance Modelling, DEM simulations and Machine Learning Approaches. Main duties and
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the air conditions in underground stations. The proposed research will be carried out with the use of Computational Fluid Dynamics (CFD) to simulate the underground station environment with the possibility
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PhD at the Forefront of Computational Solid Mechanics and Machine Learning School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Dr J L Curiel Sosa Application