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Computational Spectroscopy/Hydrogen-tunneling at elevated temperatures in the gas-phase School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof AJHM Meijer Application
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Organic quantum batteries: the development of high-performance energy storage devices (S3.5-MPS-Lidzey)
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Digitalising populations of structural systems using machine learning (S3.5-MAC-Dardeno)
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Zero-Knowledge for Quantum Proofs: Quantum Computation and Cryptographic Primitives (S3.5-COM-Abdolmaleki)
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Bugging Out: When AI loses the Plot – Detecting and Taming Hallucinations in LLM-Generated Code (S3.5-COM-Wang)
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Explainable and Causal AI for Visual Analytics in Regenerative and Climate-Smart Agriculture (C3.5-COM-Cruz Villa-Uriol)
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Adversarial machine learning - Identification and prevention of cyber-physical attacks on infrastructure (S3.5-MAC-Champneys)
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Total Cost and Environmental Footprint of Metalworking Fluids (MWFs): Quantifying the Current Landscape and Scoping Next-Generation Alternatives (C4-AMR-Secker)
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patients, the great benefits of immunotherapy can be accompanied by unwanted side-effects which can be serious and even life-threatening. Our Programme will develop an optimised digital health approach
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flares using the assumption of hydrogen recombination continuum emission, in place of a blackbody estimate. In parallel, but not in collaboration, Pietrow, Cretegnier, Druett et al. (2024) have advanced