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The project will involve both experimental and computational work and the candidate is expected to be comfortable with both. The candidate is expected to have (or be close to finishing) a Ph.D. in molecular
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an experience in technology-assisted monitoring or computational image analysis. Expected start date and duration of employment The position will start in June 2026, with exact starting date as agreed between
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Associate Professor Luca Vezzaro. You can read more about DTU Sustain at https://sustain.dtu.dk/ If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU
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, machine learning tools, and simulation techniques. If you thrive at the intersection of engineering, data, and advanced computational science, this position will allow you to contribute meaningfully
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thematic training weeks, specialist workshops, and transferable-skills courses central to the MSCA programme. Your research will be based at DTU’s Risø campus, a leading international hub for wind energy
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Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer
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creative design processes. The lab will provide access to shared resources, joint supervision, and interdisciplinary training in AI, Life Cycle Assessment (LCA), and computational design tools. The objective
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, parental leave, social security, etc.) (https://www.sdu.dk/en/om-sdu/international-staff/getting-settled ) Workplace description POLIMA is located at the University of Southern Denmark in Odense – 1h15min by
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Sustainability under the auspices of UNESCO (UCPBL: https://www.ucpbl.net/). Job description The main research area will be within the field of problem-based learning (PBL) in engineering education. The researcher
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dependable. You find enjoyment in working with data, learning new techniques, and applying them in rigorous ways. Ideally, you are at the end of your Bachelor, or start of your Master programme. In terms