492 engineering-computation-"https:"-"https:"-"https:"-"https:"-"KU-LEUVEN" PhD positions in United Kingdom
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manufacturer and technology company. Applications are invited for a 3.5-year EPSRC funded UDLA PhD studentship. The studentship will start on 1st October 2026. Project Description As Deep Learning and
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the wind/renewable energy training and research elements of the CDT programme. Funded by ESB and EPSRC, this 4 year this PhD studentship, at the University of Strathclyde is in the area of engineering and
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or mechanical engineering, specifically on end of life and life extension analysis for wind farms. The role is for the third intake of the EnerHy programme which commences in October 2026. Research project
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the Computational Science and Engineering Group’s (CSEG) goals and will proceed as a key foundational project for the new BASE Laboratory. You will be fully embedded within the M3 4Impact doctoral
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workflows and contribute to building UK capability in an important advanced reactor area. The ideal candidate will enjoy computational modelling and quantitative problem‑solving, with a strong foundation in
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backgrounds in engineering, applied mathematics, physics, computer science, or data science, and can be tailored to your interests, whether you prefer theory, modelling, or applied research. You will analyse
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, or even computational architectures. What we are looking for: Research Associate: hold a PhD (or equivalent) in Aerospace Engineering or a closely related discipline. Research Assistant: A first/masters
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electrical engineering and data science. The role is for the third intake of the EnerHy programme which commences in October 2026. Research project overview: This role offers an exceptional opportunity for a
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environment for PGRs. PGRs benefit from training through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs
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second class UK honours degree or equivalent in a related discipline. This project would suit students with an aerospace or mechanical engineering background. Experience of computational fluid dynamics