137 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" PhD scholarships in Norway
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. The project’s PI is Associate Professor Iselin Åsedotter Strønen. For more information about the project, see https://www4.uib.no/en/research/research-projects/invisible-women-of-the-sea-gendering-fishery
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systems are reshaping how we learn, work, create, lead, and participate in democracy, our centre tackles the promise and peril of hybrid intelligence—humans and machines working and learning together. Our
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with disabilities. More information about NMBU is available at www.nmbu.no/en Questions about the position Volha Shapaval Professor +47 98418248 volha.shapaval@nmbu.no Where to apply Website https
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systems to reason more coherently about ship designs, reducing ambiguity in the data available to machine‑learning systems, and supports explainability by grounding AI outputs in a known structure. This
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if you can document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme (https://www.ntnu.no/studier/phet) You must
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analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks on material design by using PyTorch or Matlab PLEASE
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https://www.jobbnorge.no/en/available-jobs/job/296771/phd-candidate-in-parasite… Requirements Research FieldBiological sciences » BiologyEducation LevelMaster Degree or equivalent Additional Information
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grade background, you may be considered if you can document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme: https
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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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(ph.d.) in artistic development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning