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immediate manager will be the Head of Discipline. About the project This PhD project focuses on advancing the modelling, simulation, and execution of complex cybersecurity scenarios within the Norwegian Cyber
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project focuses on advancing the modelling, simulation, and execution of complex cybersecurity scenarios within the Norwegian Cyber Range (NCR). The research aims to investigate how cascading cyber effects
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learning will be explored as enabling technologies for automated leakage detection and localization, analysis of complex measurements, fault-response characterization, intelligent exploration of large
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technologies for automated leakage detection and localization, analysis of complex measurements, fault-response characterization, intelligent exploration of large experimental spaces, and adaptive selection
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. While adaptation studies recognise the intertwined complexities of heterogeneous built environments and societal vulnerabilities, methodological frameworks for harnessing the interests of marginalised
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
in complex engineer-to-order shipbuilding. Realizing the full potential of AI is both a technical and an integrative challenge. It requires combining what AI excels at, such as pattern recognition and
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challenges in recent decades. While adaptation studies recognise the intertwined complexities of heterogeneous built environments and societal vulnerabilities, methodological frameworks for harnessing
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
replace or supplement traditional planning approaches, which struggles to manage the uncertainty and variability that are inherent in complex engineer-to-order shipbuilding. Realizing the full potential
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are applied in real-world settings characterized by large-scale networks, stochastic demand, operational disruptions, and complex constraints. A central research question is how machine learning can be
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. These simulations are essential for optimizing the design and placement of wind turbines in complex terrains. Multiscale approaches utilize advanced computational techniques, including nested grids and adaptive mesh