583 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" positions in Norway
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architecture. The research focus of this PhD position is the design of performant and energy-efficient Edge Artificial Intelligence (AI) accelerators. Such accelerators may be either tightly integrated with
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-state model will be approximated using machine-learning surrogates and will be used for a real-time optimization, such that the plant operates optimally despite disturbances. The candidate will be part of
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scheduling and maintenance, and the application of control and safety procedures and protocols. The successful candidate will also be required to teach fundamental fluid mechanics courses that are held in
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academic updating. At the core of the position lies the responsibility to teach main and elective courses within both the Bachelor (BFA) and the Master of Fine Arts (MFA), as well as individual supervision
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world and solutions that can change everyday life. Department of Structural Engineering We teach mechanical engineering, engineering and ICT, and civil and environmental engineering. The Department
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machine learning. Colourbox via Unsplash Colourbox What skills are important in this role? The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities
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, including individually tailored career development plans with formal supervision and project-based learning. Secondments, consortium meetings, and workshops will provide hands-on experience in collaborative
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and several centres at Faculty of Science and Technology. Read more about the faculty and departments. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/298034/phd-research-fellow
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The successful candidate will primarily teach and supervise students in the department’s
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the semantic foundation that enables AI systems to reason more coherently about ship designs, reducing ambiguity in the data available to machine‑learning systems, and supports explainability by grounding AI