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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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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 learning
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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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: 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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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