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- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- University of Oslo
- UiT The Arctic University of Norway
- University of Bergen
- Norwegian Meteorological Institute
- Norwegian University of Life Sciences (NMBU)
- The Norwegian School of Sport Sciences
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, and entrepreneurship. Doctoral Candidates will gain transferable skills and learn from industry role models, equipping them to make significant contributions to solving the AMR crisis. The succsesssful
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or machine learning frameworks Good oral and written presentation skills in a Scandinavian language at level A2 or higher Personal characteristics To complete a doctoral degree (PhD), it is important that you
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to your work duties after employment. Required selection criteria You must have a professionally relevant background in algorithms, machine learning, database systems, or data mining, with a research
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distinctions between valuable, acceptable, and non-acceptable use of these technologies in sport. The Nature and Value of Sport Virtual sports: With the help of virtual reality or computer-generated environments
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criteria Prior publications within relevant fields Strong problem-solving skills and a demonstrated capacity for innovative thinking Experience and expertise in machine learning Personal characteristics
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using machine learning or any other AI technique. Knowledge of CCS. Good oral and written presentation skills in Norwegian/Scandinavian language equivalent level B2. Personal characteristics To complete a
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required. Experience with finite-element method (FEM) and boundary-element method (BEM) is required. Experience with supervised machine learning in aeroelasticity is required. Programming skills, e.g
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on ROS2 (Robot Operating System) and best practice of use of Github. Knowledge and skills on methods in numerical optimization, machine learning, as well as knowledge on marine power and control systems
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close relation with another PhD student in Université de Lille, France. The selected candidate will have the opportunity to learn form a consortium of 8 institutions (10 Beneficiaries, 3 Partner