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Bugging Out: When AI loses the Plot – Detecting and Taming Hallucinations in LLM-Generated Code (S3.5-COM-Wang) School of Computer Science PhD Research Project Competition Funded Students Worldwide
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the key data streams and advanced analytics methods (e.g., Machine Learning) required for a practical, production-ready system. Use signal responses to optimise process parameters, tool selection, and even
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experiments and cognitive modelling. You will focus on machine learning, but will be involved in all areas. There are also spinout opportunities. For details: PhD information sheet The team have wide experience
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BBSRC Yorkshire Bioscience DLA Programme: Decoding Condensin Regulation: Single-Molecule Tools to Target IDR Interactions (CASE project) School of Biosciences PhD Research Project Competition Funded
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analytics methods (e.g., Machine Learning) required for a practical, production-ready system. Use signal responses to optimise process parameters, tool selection, and even rapidly qualify new tooling designs
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physics-based, and data-driven AI-based approaches employing neural-networks and machine learning, this project will develop and validate a multi-time scale DT concept for advanced condition monitoring and
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? This PhD project offers a unique opportunity to apply machine learning to solve a critical engineering challenge within the railway industry. The Challenge: Rail grinding is a crucial maintenance activity
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Virtual manufacturing of discontinuous fibre composites for high-performance automotive and aerospace structures (C3.5-MAC-Qian) School of Mechanical, Aerospace and Civil Engineering PhD Research
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Overview We have an exciting opportunity for a motivated and enthusiastic individual interested in biodiversity, evolution, neuroscience and machine learning to join the Leverhulme Trust funded
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species, and the emergence of previously unseen classes. Recent advances in remote sensing and machine learning provide new opportunities to address these challenges, but most current approaches