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. In Europe, these concerns have driven major regulatory developments, notably the EU AI Act and related digital sovereignty initiatives, which introduce risk- and rights-based approaches but often leave
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Laboratory (HRE Lab), providing the candidate with access to advanced experimental infrastructure and opportunities to contribute to the further development of the laboratory’s research and educational
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Developing tasks in a strong and international professional environment Career guidance and follow-up during the PhD period Open and inclusive working environment with committed colleagues Working capital
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research on digital transformation from a sociotechnical perspective, which highlights the interaction between technological development and organizational processes and concerns. The aim of the fellowship
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candidate will work with NTNU's laser-induced graphene (LIG) sensing line developing a LIG sensor system for in-situ process monitoring of fibre reinforced composite systems, and maturing it from lab-scale
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to investigate cascading cyber effects, cyber resilience, and advanced cyber range modelling. The research combines simulation, software development, and experimental validation in the Norwegian Cyber Range
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among Europe's leading universities, internationally recognized for high quality in research and education. As a societal institution, we shall contribute to sustainable and democratic development and be
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
insight into the characteristics and challenges of the engineer-to-order shipbuilding industry and develop frameworks and knowledge of AI-enhanced planning in shipbuilding supply chains. Apply quantitative
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integrated within the Norwegian Center on AI for Decision (aiD), benefiting from broad and divers expertise, and strong industrial connections. The project will have theoretical and algorithmic developments
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be developed using open-weight models. Access to model weights enables the candidate to inspect and adapt the models, investigate their internal representations, apply interpretability and verification