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Liverpool where, in the School of Computer Science and Informatics, we have an active group of PhD students, postdocs, and academics working at the intersection of Machine Learning, Verification and
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position initially and is expected to be held full time and in person. You will join the CNNP Lab, which is well supported with recent funding of over £3M. The lab is based in the School of Computing
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The primary objective of this project is to establish the evidence base on professional cycling road ‘racing’ trends and the critical tactical moments that determine how races are won. This evidence will inform future race strategy and live race tactics. Multiple factors influence the strategy...
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Please quote reference: Quantum Computing at The School of Physical Sciences Duration: 3 years and 6 months. We are currently recruiting for the following full-time, fully funded PhD studentship
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An exciting opportunity has arisen for a talented computer scientist to join our team as a researcher within the Green Algorithms Initiative in the Department of Public Health and Primary Care, one
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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School/Faculty: Computer Science Eligibility: UK/International Funding: School of Computer Science Studentship consisting of the award of fees, together with a tax-free maintenance grant of £20,780
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humans. The successful candidate will join the new Intelligent Robotics group in the Computer Science Department in the Computational Foundry in the Faculty of Science and Engineering at Swansea University
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This PhD project aims to advance Safe and Sustainable by Design (SSbD) pharmaceutical manufacturing by integrating cutting-edge methodologies, including computer-assisted retrosynthesis, end-to-end
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for extracting physiological biomarkers from ECG, PPG, and related sensor data Machine learning and AI for predictive modelling and risk stratification Computational physiology modelling to personalise and