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, computer simulations and experiments, both in fundamental and in more applied directions. The center works to advance the understanding of porous media by developing theories, principles, tools and methods
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. The HDL and SPKI research groups are part of the Centre of Research-based Innovation SFI Visual Intelligence that is a center-of excellence in machine learning research. The research groups are also active
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while maintaining energy production efficiency. The integration of machine learning (ML) in predictive maintenance has transformed hydroelectric operations by enabling data-driven decision-making and real
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UNIX/Linux interface and basic programming (e.g. Python) is a requirement. Experience with machine learning is an advantage. Experience from free energy calculations is an advantage. Applicants must be
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. Your main tasks will be Develop and apply machine learning techniques and statistical analyses, including novel methodology for analysis of complex polygenic traits and prediction tools for precision
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understanding of adaptive immune receptor (antibody and T-cell receptor) specificity using high-throughput experimental and computational immunology combined with machine learning. The long-term aim is to
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relevant experience in the development and deployment of machine/deep learning models as well as the use of remote sensing data You must have relevant experience in the development of hydrodynamic and water
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degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system is required. The candidate must have interest and solid background in software systems, machine learning
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the Head of the Computing Group. Duties of the position Acquire and maintain cutting-edge knowledge of the field Coordinate with the supervision team to agree on research directions Actively participate in a
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be employed by any other institution for the time of the fellowship. Experience with AI-related research and/or innovation is an advantage. Experience in machine learning is a requirement. Experience