15 professor-computer "https:" "https:" "https:" "https:" "https:" "Dr" "University of Aberdeen" PhD positions at University of Surrey
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October 2026. Later start dates may be possible, please contact Dr Chatterjee once the deadline passes. You will need to meet the minimum entry requirements for our PhD programme . The successful candidate
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Quantum materials underpin key emerging technologies in quantum computation, sensing, and low-energy electronics (e.g. topological insulators, topological superconductors, spin liquids, superfluid
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. Supervisors:Professor Paul Sellin , Professor Carol Crean and Dr Ian Riddlestone Entry requirements Open to candidates who pay UK/home rate fees. See UKCISA for further information . Starting in October 2026. You will
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for applicants with a degree in Computer Science, Mathematics, Physics, or Engineering. Prior experience in AI is necessary. Prior experience in tomographic imaging and medical physics would be advantageous but
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and reporting requirements, under appropriate data, IP, and publication governance. The work also aligns with Surrey’s GAIN programme and games provision within SAHCI, and will support standards
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, distributed systems, and trustworthy AI, with implications for regulatory compliance and real-world deployment of federated systems. Supervisors:Dr Pedro Porto Buarque de Gusmao and Dr Frank Guerin Entry
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-leading research programme investigating key nuclear reactions for both fundamental physics and applications. The aim of the project is to establish new methods to measure properties of Auger electron
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2026. Later start dates may be possible, please contact Dr Eran Ginossar once the deadline passes. You will need to meet the minimum entry requirements for our PhD programme. Desired experience
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for applicants with a degree in Computer Science, Mathematics, Physics, or Engineering. Prior experience in AI is necessary. Prior experience in tomographic imaging and medical physics would be advantageous but
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applications where labelled data is scarce, enabling models to learn from the data itself without relying on extensive human annotation. Supervisors: Dr Donya Hajializadeh, Dr Fernando Madrazo-Aguirre, Dr Sara