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15th December 2025 Languages English Norsk Bokmål English English Molde University College announces PhD scholarship in Logistics focusing on Optimization and assessment of carbon capture Apply
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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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on pre-existing/collected data using Supervised/unsupervised fine tuning of the existing models (e.g., Retrieval-Augmented Generation, Low-Rank Adaptation, Direct Preference Optimization, Reinforcement
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Supervised/unsupervised fine tuning of the existing models (e.g., Retrieval-Augmented Generation, Low-Rank Adaptation, Direct Preference Optimization, Reinforcement Learning from Human/AI Feedback). Moreover
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the sensory and functional qualities of natural seafood. This PhD project is expected to develop technology for cultivated seafood, by selecting the optimal cell source, developing a continuous cell line and
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they support running optimally under any given circumstances. Artificial intelligence in networking, i.e., applications of AI to improve network performance, maintainability, security, automated repair and other
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opportunities in combining physical meteorological/hydrological/hydraulic modelling and AI methods to improve the inflow prediction, and optimize the control of and use of water in the water courses considering
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in crystalline rocks. Drilling optimization using machine learning, e.g. predicting rate of penetration (ROP) and wear. Investigate the possibilities in automation and robotization and the use
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stresses, drill wear (bit replacement). Collect and analyze existing and new data on drillability related to mineral content and degree of metamorphosis in crystalline rocks. Drilling optimization using
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organizational challenges of this twin transition. First, interoperability is key in the energy transition, requiring further integration of existing control and optimization systems. This transition makes energy