12 machine-learning "https:" "https:" "https:" "https:" "https:" PhD scholarships at NTNU Norwegian University of Science and Technology
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position Distributed machine learning takes advantage of communication and
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to machine learning. This PhD provides a unique opportunity to shape emerging concepts in Artificial Intelligence Informed Mechanics (AIIM), combining fundamental research with methodological innovation. You
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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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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
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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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), it is important that you are able to: Ability to work independently and in a team. Drive to learn new methods and applications. Curiosity and creativity in finding problem-related solutions. Contribute
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to research, development and demonstration of a methodology for building and integrating machine learning solutions for past technical artefacts. Contributing to the development of holistic view of product
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selection criteria Experience with machine learning or other relevant AI technologies Experience with condition monitoring, preferably within maritime domains Knowledge of ship machinery and systems Good oral
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Computer science Engineering » Computer engineering Technology » Information technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 10 Feb 2026 - 23:59 (Europe/Oslo
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, target recognition and shape estimation, data association, as well as intention prediction, beyond the state of the art. In order to support machine learning, the project will make use of historical radar