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marine technology, together with more than 60 PhD students from all over the world. You will explore how emerging AI technologies—foundation models, generative design tools, agent platforms, reasoning
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real-time rerouting recommendations. Beyond the PhD, the project’s data-driven models will evolve through continuous real-world updates, contributing to sustainable aviation practices and climate-aware
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the broader framework of Embodied AI. The goal is to integrate physical models with deep learning to create interpretable, data-driven observers that enable physically grounded perception and control for robust
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this impact; You have experience and/or willing to learn quantitative modelling, risk assessment, and ESG evaluation; Experience with data-driven decision-making tools and frameworks is an asset; Proficiency in
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loading conditions. By generating datasets from finite element simulations, ML models can learn the mapping between unit cell design parameters and homogenised properties. State-of-the-art approaches
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At the Faculty of Engineering and Science, Department of Materials and Production one or more positions as PhD stipend in Artificial Intelligence for Autonomous Systems, within the doctoral
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22nd December 2025 Languages English English English The Department of Engineering Cybernetics has a vacancy for a PhD Candidate PhD Candidate in Physics-Informed RNNs for Autonomous Navigation and
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FOR THE HIRING OF AN INITIAL LEVEL PHD, "PROFIT – PRocedure Optimization and data-driven eFficiency Improvement in healthcare environmenTs" PROJECT, IN AN EMPLOYMENT CONTRACT WITH AN UNCERTAIN TERM, FACULTY
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between wind farms and MS motivating our central research questions: “do turbine driven changes in the MBL promote or hinder MS formation?” and “how does this modified rate of MS formation affect the
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and their components. Experience in modelling distributed energy resources, optimization and decision making, and district level energy management. Experience in data-driven modelling, AI techniques