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AI-driven creativity with clear environmental performance feedback early in the architectural design process. This phase is characterized by high uncertainty in data availability and design parameters
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Environments within the general study programme Electrical and Electronic Engineering; as per March 1, 2026, or as soon as possible thereafter. The candidate will be based in Aalborg at the Automation and
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, fatigue, corrosion, and biofouling ) of subsea structures. Derive limit state functions associated with the failure mechanisms using high-fidelity Finite Element Analysis. Perform sensitivity and
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by a collaboration partner Perform a comprehensive CFD-based sensitivity study to reliably assess the impacts of key sub-models (e.g., green fuel combustion mechanisms, radiative heat transfer
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decision-making. A main challenge is finding ways to link AI-driven creativity with clear environmental performance feedback early in the design process. This phase is characterized by high uncertainty in
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, machine learning, and decision-making methodologies to design systems capable of functioning safely and efficiently under uncertainty. Limited teaching within the Global Business Engineering program can be