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Materials, mastering scientific machine learning, uncertainty quantification, and high-performance computing. Your models will inform fusion design and advance AI-for-materials. Perfect for physics, maths
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mathematical techniques to problems with global significance. Interdisciplinary Training – Students gain expertise across physics, engineering, computer science, and applied mathematics, developing versatile
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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in Chemistry, Physics or related subject. The selected PhD candidate will work with Prof Elena Besley on computational modelling of next-generation semiconductors made from atomically thin materials in
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) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and
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to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video unable to load from YouTube. Accept cookie and refresh page to watch
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advancement in electric machine performance. Who we are looking for We seek a motivated candidate with at least a high 2:1 degree in Engineering, Physical Sciences, or a related field. Prior experience (such as
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10th April 2026 Languages English English English The Department of Mechanical and Industrial Engineering has a vacancy for a PhD Candidate in bioinspired randomly featured materials Apply
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of the Built Environment, Division for Building Technology, Management and Indoor Environment, Research Group for Building Physics, which carries out research in these main areas, with focus on the performance
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headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here