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research environment at the Department of Engineering Cybernetics, renowned for its leading expertise in optimization, control, and artificial intelligence for cyber-physical systems. Are you motivated
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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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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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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
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transition. First, interoperability is key in the energy transition, requiring further integration of existing control and optimization systems. This transition makes energy forecasting particularly critical
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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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and research, in and outside academia. About the project The proposed research aims to optimize the design of timber building systems with innovative connections and achieve an extended service-life
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code compilation, which offer a modular approach to domain-specific optimizations. Your project is expected to contribute to cutting-edge research initiatives leveraging, analyzing, and exploiting
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fuel cells with the vessel’s onboard DC distribution grid (1-1.5 kV or even MV) require power electronics, which enable power and voltage control. Designing high-efficiency and low-footprint power