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C. Yin, P. Xiao, V. Sharma, Z. Chu, Garcia-Palacios, Machine Learning Based Physical Layer Security for Detecting Active Eavesdropping Attacks, IEEE Commun. Lett., 1-5, 2025. Bowman, T., Georgalas
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, G. et al. Machine learning and wearable sensors for automated Parkinson’s disease diagnosis aid: a systematic review. J Neurol 271, 6452–6470 (2024). https://doi.org/10.1007/s00415-024-12611-x Nayan
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learning experiences that prepare graduates to excel in an ever-changing world. We are seeking a new Pro-Vice-Chancellor, Education to play a pivotal role in shaping Surrey's education and student experience
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Supervisor: Professor Fernanda Duarte Start date: 1st October 2026 Applications are invited for a fully-funded DPhil studentship in Machine Learning Interatomic Potentials for Metal-Ligand
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, student engagement and supporting the development of future FinTech professionals. In this role, you will: Teach at undergraduate and master’s level, including lectures, seminars, tutorials and computer lab
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students and supporting their academic development. In this role, you will: Teach undergraduate students through lectures, seminars, tutorials and computer lab sessions. Act as a personal tutor, providing
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, student engagement and supporting future data scientists and statisticians. In this role, you will: Teach undergraduate students through lectures, seminars, tutorials and computer lab sessions. Act as a
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Project description Electromagnetic (EM) sensing is emerging as a powerful enabling technology for modern high-value manufacturing. Advances in computing power and machine learning now allow us to
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-invasive diagnostic test for motor neuron disease (MND). You will join a multi-disciplinary team of neuroscientists, MR physicists, neuroradiologists and computer scientists and will be primarily responsible
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with the CDT’s aim to achieve a sustainable wind farm lifecycle by developing methods for high-value reuse of composite turbine blades. Machine learning and non-destructive evaluation techniques will be