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, predictive modelling, and autonomous maintenance solutions. You thrive on scientific discovery, enjoy tackling complex multi-physics problems, and have the drive to explore innovative concepts
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, and ambitious researcher committed to accelerating the green transition by advancing adaptive materials, predictive modelling, and autonomous maintenance solutions. You thrive on scientific discovery
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student to work within the ADaM project (Autonomous workflows for Data-driven first-principles Modelling). The project will leverage Large Language Models (LLMs) as active software agents to help automate
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challenges in the renewable energy sector. The programme focuses on advancing intelligent meta-materials, digital twinning, autonomous monitoring, and risk-informed decision methodologies that will contribute
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, digital twinning, autonomous monitoring, and risk-informed decision methodologies that will contribute to safer, more efficient, and more sustainable energy systems. Upon completing the programme, you will