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Norwegian yards: Efficient operations through digital twins and artificial intelligence”. The project aims to contribute to the growth and competitiveness of Norwegian yards in the global offshore wind
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of artificial intelligence. Electric drilling and other methods for reduced climate footprint. Combine deep wells with shallow seasonal heat storage (GeoTermos) and possibly short-term storage (accumulation in
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machine learning, e.g. predicting rate of penetration (ROP) and wear. Investigate the possibilities in automation and robotization and the use of artificial intelligence. Electric drilling and other methods
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, optimization, and artificial intelligence, with potential applications in energy systems, and infrastructure networks. The successful candidate will become part of a dynamic and internationally connected
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Master's degree in Computer Science, Artificial Intelligence, Data Sciecnce (with a focus on machine learning) or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120
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to your work duties after employment. Required selection criteria You must have a relevant Master's degree in Computer Science, Artificial Intelligence, Data Sciecnce (with a focus on machine learning
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to contribute to foundational research at the intersection of control theory, optimization, and artificial intelligence, with potential applications in energy systems, and infrastructure networks. The successful
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Aker BP. Big data, Internet of Things (IoT) and artificial intelligence (AI) represent key enablers of the digital transformation. The main objectives of the project include the development and the
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for offshore wind at Norwegian yards: Efficient operations through digital twins and artificial intelligence”. The candidate will be part of the Production Management research group at NTNU’s Department
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of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Work and/or research experience in machine learning, artificial intelligence, cable technology and/or