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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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administrative workload, the standardization of complex assessments, and reduced professional discretion. There is therefore a need for more research examining how digitalization unfolds in practice. The PhD
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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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period of 3 years. The position is subject to external financing through the RCN funded project "Quantum Oscillator Networks for Optimisation and Machine Learning" (project number 358752). About the
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environmental data from open, citizen and municipal sensor networks, AI-assisted analysis, simulation, visualisation and stakeholder deliberation. This workflow will be tested in a primary living lab, preferably
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to specialized courses, networking opportunities, and a broad national research community. The successful candidate will be expected to contribute to EPINOR's research and training activities and help strengthen
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international research proposals. Collaborate across disciplines within Mission Mjøsa and relevant external research networks. Strengthen NTNU’s position within digital twin research, semantic interoperability
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to complex climate risks. Your main duties and areas of responsibility will be to co-design and implement innovative science-policy engagement processes design and administer surveys and participatory research