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remains dominated by case-specific studies and expert-driven intuition. This project aims to close that gap by generating, extracting and measuring corrosion data into a unified knowledge base. On the
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develop quantitative methods to estimate effects on infrastructure degradation, maintenance needs, operational risk, punctuality and costs. The aim is to develop and validate a practical, transparent
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other components. The PhD candidate will link TrainGate detections and early warnings with maintenance, incident, operational and cost data and develop quantitative methods to estimate effects
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industries. Our research includes developing concepts for renewable-driven technologies and system solutions to decarbonize the chemical and energy industries, including carbon capture, utilization and storage
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. Knowledge of renewable energy systems (hydropower, wind, solar) and their grid integration. Experience in mathematical modeling, optimization algorithms, and data-driven methods. Possess a strong academic
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design spaces, long-duration simulations, and real-time applications. This PhD project will develop physics-informed deep learning and surrogate modelling approaches to accelerate simulation, uncertainty
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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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. Our research includes developing concepts for renewable-driven technologies and system solutions to decarbonize the chemical and energy industries, including carbon capture, utilization and storage
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
knowledge of AI-enhanced planning in shipbuilding supply chains. Apply quantitative methodologies, such as simulation, analytical modelling, and AI‑driven techniques, to develop decision support for efficient
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
methodologies, such as simulation, analytical modelling, and AI‑driven techniques, to develop decision support for efficient planning and coordination of production activities in supply chains and generate