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collaborative studentship between the University of Edinburgh and the National Quantum Computing Centre (https://www.nqcc.ac.uk ). The position will be registered and hosted at the University of Edinburgh and
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excellent understanding in power system dynamics, power electronics and control. Experience in working with power systems dynamic simulation will be helpful, but not necessary to apply for the position. How
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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the areas of fluid dynamics, turbulence and net-zero combustion. There is substantial scope for the student to direct the project with the main focus on (i) Generating an advanced Direct Numerical Simulation
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both homogenous and heterogenous catalytic conversion, including the handling, testing and characterizing the catalysts as well as the reactor and process simulation and analysis. Details will be
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verification of resilient state estimators for the eVTOL and HESS. Essential and Desirable Criteria - Background: control/mechanical/electrical engineering, physics or computer science - Essential knowledge
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, while simulations are subject to error due to uncertainty in nuclear data and unresolved physical processes e.g. thermal expansion and fine-scale inhomogeneities. Generating independent simulation
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local gas/liquid phase conditions. Whilst direct simulations of breakup are possible, computational cost is high, restricting applications to small sections of geometry and for modest run times
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defined by Swansea University) in Engineering, physical sciences or similar relevant science discipline. We also welcome applications from graduates in computational science or mathematics. Note for
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state-of-the-art high heat flux testing, simulating the extreme environments of fusion reactors. Harness advanced computational tools to model complex particle-material interactions and predict material