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Design of a Fault Detection System for AI-Assisted Adversarial Attacks on Industrial Control Systems
AI-assisted adversarial attacks. You will work on topics such as cybersecurity, intrusion detection, adversarial machine learning, industrial automation, digital twin technology, and reinforcement
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Characterisation" "Data Science and Machine Learning in Materials" "Plastics Recycling and Circular Economy" Research theme: "Materials Characterisation" "Data Science and Machine Learning in Materials" "Plastics
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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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of computational optimisation, machine learning, and experimental design of new chemistry. You will develop Bayesian optimisation and other active learning approaches for experimental design with a focus on real
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to the new theoretical development of graph deep learning, and contribute to the research community of brain connectivity and network neuroscience. This is a joint Phd studentship between Coventry (UK) and
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vision, robotics, machine learning and natural language processing (CSRankings) and were 7th in the UK for REF2021 outputs in Computer Science research. CVSSP and Computer Science are at the core of the
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associate to work with Dr Timothy Rittman on the implementation of machine learning for understanding and clinical utility. The role will involve the collation and curation of datasets of neurodegenerative
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Shrivenham and will undertake high-quality scholarship and support a range of professional military and security education courses at the postgraduate level. Successful candidates will teach and supervise
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: Erlangen Programme for AI” This is a 5-year programme supported by the EPSRC and is a collaboration of mathematicians and computer scientists at the University of Southampton, the University of Oxford (lead
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continuous programme improvement. Participate in educational initiatives and activities to enhance student learning outcomes. Requirements: A PhD or a Master’s degree (with significant industry experience) in