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Norwegian University of Science and Technology (NTNU) for general criteria for the position. Personal characteristics Ability to work independently and in a team Drive to learn new methods and applications
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volumes, there is a plan to utilize modern machine learning strategies like "physics-informed neural networks." One of the main advantages of this approach is that measurements and observations made
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these powerful tools, and support learning in disciplinary or interdisciplinary contexts. In addition, the nature of the interaction between human and machine triggers new questions about the locus of agency and
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: The main place of work will be at our campus in Halden, but some presence at our campus in Fredrikstad may be expected. Project description Project title: My AI Co-worker: Exploring AI for Computer Supported
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will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning
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physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or equivalent) in
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data collection approaches. Familiarity with or strong motivation to learn machine learning or advanced data analytics for pattern detection and forecasting in environmental data. Familiarity with
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material design process. Some potential key research objectives: AI Model Development: Create machine learning models to predict FGM properties based on compositional gradients and processing conditions
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advertisement About the position A position as Researcher in Natural Language Processing (NLP) is available in the Language Technology Group (LTG) within the Section for Machine Learning at the Department
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invites applicants for four PhD Fellowships in subsurface characterization within geosciences, reservoir engineering, molecular modelling, and machine learning at the Faculty of Science and Technology