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and specialising in flood-risk evaluation, geohazard assessment, and sustainable drainage solutions across the UK, China, and Australia. This research develops a data-intensive, AI-driven framework
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to augment the funds to cover the extra costs associated with international student fees. Exceptional candidates may be eligible for an International Fee Bursary. High throughput kinetics data for steel
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and Technology (CST) at the University of Cambridge. The goal of this PhD programme is to launch one "deceptive by design" project that combines the perspectives of human-computer interaction (HCI) and
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) advances in imaging techniques that fuel a more detailed understanding of the brain, 2) tools from artificial intelligence that enable building better computer simulations of the brain. The lab will leverage
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use and contribute to the Lean4 proof assistant, where we build foundational technology such as a powerful BitVector library, coinductive proofs, an embedding of MLIR's SSA data structures into Lean
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statement that shows evidence of engagement with this advert. Further information on the PhD in Computer Science programme can be found at: https://www.cst.cam.ac.uk/admissions/phd All applications should be
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work. Fixed-term: The funds for this post are available from 1st February 2026 until 31st January 2029, in the first instance. To apply online for this vacancy and to view further information about the
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biostatistics. We develop, apply and promote innovative statistical and data science approaches to advance biomedical science and human health. The BSU current research portfolio is organised into five main
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for the course "PhD in Chemistry", naming Professor David Spring as potential supervisor. Information about research in the Department of Chemistry is given at: http://www.ch.cam.ac.uk For any queries about this
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, defensible datasets that can verify precious metal article authenticity. Greater data will enable smart approaches with assigned probabilities of authenticity to aid hallmarking practices. Partnering with