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Field
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effort at the intersection of machine learning and applied mechanics. The focus of this position is on extracting information about what a neural network has learnt in a symbolic and (human) interpretable
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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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physics, with expertise spanning both observational studies and theoretical or computational modeling. It offers an international and collaborative work environment that values equality, diversity
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to improve structural durability, reduce material consumption, and support the UK’s net-zero goals. Funding notes: The position includes a full scholarship for UK-based PhD candidates and a half-scholarship
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will generate unprecedented volumes of data, to be processed at a central facility, and distributed to a global network of SKA Regional Centres (SRCs) for storage, access, and scientific exploration
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, University of London in August 2024. As a PhD candidate, you'll become an integral part of the School of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading
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directions will be pursued to enhance column generation using machine learning. The first line of research focuses on improving scalability by using Graph Neural Networks to identify and eliminate non
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to coordinate and conduct asset management and maintenance activities across infrastructure networks in the Netherlands. Together with our research partners from Next Generation Infrastructure network, the PhD
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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and