652 phd-studenship-in-computer-vision-and-machine-learning PhD positions in United Kingdom
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How to apply: uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded for home students or EU students with settled status; the successful candidate will receive a tax-free stipend set at
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Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM) at the University of Nottingham. The student will work in
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Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM). The student will work in
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. The exact reasons for this remain unclear. This is an exciting project suitable for an enthusiastic and passionate PhD candidate aiming to explore the link between CF and cardiovascular/cerebrovascular health
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the solution of governing PDEs. - Train machine learning models to predict lifetime and failure based on loading and environmental histories. The PhD student will have access to world-class computing facilities
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requirements for our PhD programme . Candidates should have a strong background and first degree in chemistry or pharmaceutical sciences or a closely related subject (BSc/MChem/MSc). Industrial experience
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fees for the period of the relevant programme as outlined in the offer letter (usually three years). CSC will provide living allowances as prescribed by the Chinese Government, and will cover the round
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Deadline: 31 August 2025 A fully funded four-year PhD position is available to work on the project titled “Real-world quantum verification and benchmarking of noisy hardware”. This position is a
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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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, to industrial catalysis and green energy production. This PhD project offers a rare opportunity to explore hydrogen surface collisions at a fundamental, molecular level to gain unprecedented insight into the role