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) Applications are invited for a three-year PhD studentship. The studentship will start on1st Jan, 2026. Project Description Glioblastoma (GBM) is the most aggressive and treatment-resistant form of brain cancer
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candidates will have a PhD (or equivalent experience) in Computer Science, electrical engineering, or other related quantitative subject. They will have a strong understanding of computer science (hardware and
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sits at the cutting edge of materials science and solid mechanics, using real-world microstructure data to simulate thermo-mechanical behaviour at the grain scale. Your work will form a key part of a
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Closing Date Sunday 17 August 2025 Reference PHD002-25 A funded PhD position is available on a project funded by the Leverhulme Trust. Description below: The density of information content in screen media
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees
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A funded PhD position is available on a project funded by the Leverhulme Trust. Description below: The density of information content in screen media – i.e., the light, volume and pitch changes from
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available, tailored to the needs and aspirations of the successful applicant. More information on the academic supervisor and EDC collaborations with JLR is available here: https://www-edc.eng.cam.ac.uk
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of our key research directions relevant for this position. Candidates should have (or be near to completing) a PhD in Computer Science or a related subject, or relevant experience. A high degree of
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
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Grand Tours, one-day races (monuments and semi-classics), and select World Tour 1-week stage races. The data sources will include video and previous race commentary to ‘code’ key events in races that help