62 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at NTNU Norwegian University of Science and Technology in Norway
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to SAFE. Delivering EVU course from SAFE center. Required selection criteria A PhD degree (or equivalent) in biometrics, information security, computer science, electrical engineering, or machine learning
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» Autonomic computing Engineering » Maritime engineering Technology » Computer technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 25 Apr 2026 - 23:59 (Europe
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(s) Number of offers available1Company/InstituteDepartment of Computer ScienceCountryNorwayCityGjøvikPostal Code2815StreetTeknologivegen 22Geofield Contact City Gjøvik Website http://www.ntnu.no Street
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Digital. The research focuses on advanced signal analysis and machine learning methods that enable robust operation and service continuity in future wireless networks under challenging radio conditions. As
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acquire such competence during the employment period. In such cases, you will also be assigned relevant teaching as part of the career-promoting work. The appointment is to be made in accordance with NTNUs
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area on civil security by focusing on the vulnerability assessment of urban environments, sustainability, resilience, and knowledge for a better world (https://www.ntnu.edu/civil-security ). Duties
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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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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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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