Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
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 Description This is NTNU NTNU is a broad
-
Country Norway Application Deadline 12 Oct 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
-
Country Norway Application Deadline 12 Oct 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
-
: Contribute to the definition and vision of smart grid reliability Develop and evaluate modern methods for power system protection and control Advance the knowledge on grid protection, control and automation
-
for Applied and Theoretical Econometrics (CATE). The doctoral programme is an important element in the department’s research excellence strategy and in BI’s vision to become one of the leading research business
-
that you are particularly suitable for a PhD education. You must meet the requirements for admission to the Faculty of Engineering https://www.ntnu.edu/iv/doctoral-programme . For communication and co
-
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description About the position Faculty of Environmental Sciences and Natural Resource
-
relevant background in Marine Technology, Ocean Engineering, Marine Hydrodynamics or equivalent. Your education must correspond to a five-year Norwegian degree program, where 120 credits are obtained
-
criteria professionally relevant background in Mechanical Engineering, Marine Engineering, or Mechatronics education must correspond to a five-year Norwegian degree program, where 120 credits are obtained
-
-based control and decision-making for complex multi-agent systems. The project explores new computational frameworks that combine principled reasoning with the efficiency of modern machine learning