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us to run large numerical simulations with billions grid points on mixed computer architectures including CPU and GPU machines. A current project is preparing the code set for the next generation of
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to support condition-based predictive maintenance for gas turbine engines. Cranfield has developed unique physics-based technologies on gas turbine performance simulations, diagnostics, prognostics and lifing
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in healthcare service and opportunities for identification of such deviations using computer vision approaches. It will demonstrate how deviation data can be used in computer-based simulation models
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to study corrosion, cracking and mechanical degradation, develop advanced computational models using modern C++ and high-performance computing to simulate material behaviour over a 100+ year timespan. This
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and theoretical and computational collaborators. Your experience and ambitions Interest in experimental condensed matter physics – especially in superconductivity and magnetism. Proficiency in searching
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. This project seeks to enhance the phase-field method, enabling more accurate predictions of fracture under dynamic conditions. State-of-the-art computational techniques combined with insights from advanced
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-efficient research that prevents fatigue failures has pushed towards integrated computational materials engineering approaches that improve competitiveness. These approaches rely on physics-based models
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– please select 2025 Funding (page 8 on the application process) In the event you have already applied for the above programme previously, the application system may issue a warning notice and prevent
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II CDT) at the University of Warwick, where you’ll be immersed in a community dedicated to computational science innovation. With expert training in atomistic simulation, machine learning, and high
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@lancaster.ac.uk with: a current copy of your CV; a covering letter explaining your motivation for applying to the programme; an up-to-date copy of the degree courses you have studied including marks awarded