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, or multi-physics simulation. Experience and skills · Ideally 3–5 years of experience (including PhD) in one or more of the following: o Finite Element Modelling (FEM), o Multiphysics
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) Corrosion behavior (electrochemistry & high-temperature oxidation) In-situ monitoring of AM processes Computational skills in: Phase-field modeling, Machine Learning, FEM, DEM, COMSOL Alloy design (CALPHAD
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Completion or near completion of a PhD in Engineering (mechanical, aerospace, civil, petroleum) or Science (applied physics, applied mathematics) with a strong background in CFD and the finite element method
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for the production of heat pipe components Your Profile: Completed university degree in mechanical engineering, physics, materials science, computational engineering, or a related field, with a PhD or Master degree
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This 4-year PhD programme is fully funded for home students; the successful candidates will receive a tax free stipend based on the UKVI rate (£20,780 for 2025/26) and tuition fees will be paid
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motivated PhD student to join our interdisciplinary team to help address critical challenges in high-speed electrical machine design for electrified transportation and power generation. Together, we will make
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into electric propulsion systems, composite materials, and advanced simulation technologies. Vision We are seeking a highly motivated PhD student to join our interdisciplinary team to help address critical
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imposed timelines/milestones. PhD (or near completion) in Engineering or Applied Science with strong expertise in CFD. Proficiency with open-source engineering software and numerical methods such as FEM
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Organisation Job description PhD position: ML based implementation of constitutive behavior of stainless steel Metal forming is a widely used method to form steel products efficiently in mass
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Organisation Job description PhD position: ML based implementation of constitutive behavior of stainless steel Metal forming is a widely used method to form steel products efficiently in mass