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modelling, and high-performance computing. The position offers close supervision, access to modern computational infrastructure, and collaboration opportunities across disciplines — from mechanics to machine
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25th February 2026 Languages English English English The Department of Materials Science and Engineering has a vacancy for a PhD Candidate in machine learning and large language models (LLMs
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state-of-art research training to post-doctoral fellows, Ph.D. and Master students in the field. For more information about the center, please visit http://csiss.gmu.edu/. George Mason University College
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researchers, both locally and abroad. Your immediate leader is Trine Aakvik Strand For more information about NorHead, visit: https://www.ntnu.no/norhead/ About the project Chronic migraine affects millions
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Interaction (HCI). The position will collaborate closely with (1) the NTNU Shore Control Lab (SCL), a design and human factors research environment focusing on human-centered design of technology for safety
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 2 months ago
of material deposited, while maintaining the expected accuracy. Part of the activity will also involve implementing Artificial Intelligence (AI) methods similar to computer vision to facilitate this prediction
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» Programming Engineering » Computer engineering Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 26 Apr 2026 - 23:59 (Europe/Oslo) Country Norway Type
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Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning or other relevant AI technologies Scandinavian
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. Diversity Diversity is a strength, and at NTNU we aim to be an employer that reflects the diversity in society and that makes use of the potential of the population's collective skills. Our vision is
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strategy; on how the wars were prepared, experienced and remembered; and on how peace was made. BLOCKADE sets out to prove that these blockades are crucial to understanding not only the way the world wars