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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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partner universities in Denmark as well as abroad. The ideal candidate will bring to the project: MSc in Civil Engineering preferably with focus on Wind Engineering, Computational Fluid Dynamics and/or
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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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relevant Engineering discipline, or a related field. Foreign degrees must correspond with the admission criteria for the PhD program. Candidates submitting MSc thesis within 30. June 2026 may be considered
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engineering, building physics, material science, data science, or a related field. Foreign degrees must correspond with the admission criteria for the PhD program. Candidates submitting M.Sc. thesis within 30
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-driven model selection, and deep learning for data analysis and feature extraction from characterisation data. Surrogate modelling will be employed to reduce computational costs, and AI-based uncertainty
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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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. This project aims to uncover fundamental "algorithms" the mammalian brain uses to predict or choose between dynamically moving agents, working at the intersection of ethology, computational behavior and systems