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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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physics, and would suit a mathematically inclined student with a background in theoretical physics or mathematics. Prior exposure to quantum field theory, string theory, or related areas is helpful but not
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implementation of decentralised personal data governance frameworks? Technology: How can multimodal knowledge graphs in combination with generative AI help individuals govern their data (e.g. within decentralised
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) in mathematics, computer science or a related discipline. This research is interdisciplinary. The candidate must have strong expertise in at least one of the following areas (1) or (2), and a clear
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
intelligent methods that integrate large language models (LLMs) and knowledge graphs to interpret technical documentation and structure complex engineering knowledge. The goal is to create digital twins
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context. The work will include, but is not limited to: investigating new mathematical formulations of the underlying physics; developing fast algorithms and numerical methods that leverage modern parallel
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of the assembly of these complex microbial communities using ecological theory and mathematical models. The questions we address are: (1) how does the microbial community change during cultivation
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to focus on the relationship between geometry and quantum theory. A key objective will be the conceptual and mathematical understanding of the original Penrose spin network, with a view toward foundational
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
placement with Rolls-Royce. The research focuses on AI-driven digital twins, using large language models and knowledge graphs for predictive maintenance in aerospace systems. Aerospace systems generate vast