328 computational-physics-"https:"-"https:"-"https:"-"https:"-"Caltech" positions at University of Sheffield
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Numerical simulation for thermoplastic composites overmoulding process
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Generalisable, Physics-Aware Machine Learning for Gas Turbine Engines
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online provision of the pre-sessional courses you will need: a modern laptop or desktop computer in very good working order (Windows 11 or macOS Tahoe 26.1 preferred) a headset (strongly recommended) or
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subjected to a typical loading scenario. This research will benefit from excellent computing facilities, expertise in computer-aided engineering (CA2M lab), the available experimental facilities including
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professional reasons in an academic environment. The course is roll-on/roll-off with students staying for a minimum of two weeks. It runs separately from our large pre-sessional programme. Duties also include
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of such program could be done in case of it was necessary. For instance, for the linkage of new material models or certain numerical features such as a new finite element. This research will benefit from excellent
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Relevant Discipline. • Experience in numerical modelling/materials. • Strong mathematics, physics, and computer programming skills. If English is not your first language, you may be required to provide
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Vision solutions to showcase potential process improvements to manufacturing companies. You will work alongside other Engineers to deliver research that has real-world benefits. You will be a student
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computational implementation and validation against experimental observations. The PhD offers in-depth training in multiphysics modelling, computational mechanics, and high-temperature material behaviour
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to access a wide range of opportunities and events. It also plays a key role in our reporting, helping to drive data-driven decision-making across our programme of engagement and fundraising activities. You