633 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" "St" positions in Norway
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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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doctoral degree in cryptography or a related area. Good oral and written presentation skills in English. The ability to teach courses at the department (https://wiki.math.ntnu.no/emner ). PLEASE NOTE: For
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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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Qualifications and personal qualities: Applicants must have a PhD in sociology. Applicants must have experience and expertise in qualitative methods and be able to teach qualitative methods at both undergraduate
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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
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shocks from the past and places them into a future scenario. What can we learn from the past to improve future climate projections and preparedness? It will drastically expand the available evidence by
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to the international initiative “Antarctic InSync.” For more information, see: https://ic3.uit.no/ . The position is based in the Marine Ecology section of the Research Department and will involve collaboration within a
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-2033). The center's overall goal is to develop new, empirical knowledge about the role professional language plays in society and how professional language functions, is learned, and used in different
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learning. The successful candidate will be expected to engage in all of these activities. In collaboration with the science education research groups at the faculty, the candidate will gather and analyse
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schemes and reduce economic harm. Consequently, organizations are now looking to artificial intelligence (AI) to enhance AML capabilities. AI-driven solutions can learn from vast datasets to spot hidden