591 phd-studenship-in-computer-vision-and-machine-learning PhD positions in United Kingdom
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to achieve, at least a 2.1 honours degree or a master’s in a relevant science or engineering related discipline. Applicants should have strong background in Machine Learning and Deep Learning. To apply, please
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Location: UK Other Applications are invited to undertake a PhD programme, in partnership with Airbus, to address key challenges in ensuring adoption of sustainable approaches to fuel additives
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which there exists extensive experience in the areas of machine learning, biostatistics, and medicine: Dr Yanda Meng and Dr Tianjin Huang (Machine Learning), Prof Yalin Zheng (AI in Healthcare), A/Prof
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Sh.24.3 PhD in Sound Analysis for Predicting Category 1 Ambulance Calls School of Computer Science PhD Research Project Competition Funded UK Students Dr Ning Ma, Prof Jon Barker Application
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Fees for 4 years (Full time), £12,000 stipend for 3 years We are pleased to invite applications for a funded PhD studentship exploring how a curated Arts Public Programme can address pressing issues
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applying to the Computer Science PhD programme, supervised by Dr Ashley Fraser. For your application, you will need: Two-page CV with names and contact details of two referees (one must be academic). In
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models, making the use of data-driven approaches a promising direction. This PhD project will investigate the use of data-driven and machine learning approaches, both measurement based but also model based
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or computational modelling is desirable but not essential; applicants should demonstrate strong academic performance, resilience in the face of research challenges, a proactive attitude to learning and a willingness
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Deadline: 31 August 2025 A fully funded 3.5 year PhD position is available to work on the project titled “Scalable benchmarking for digital quantum computers based on blind testing”. This position
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Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Behaviour-Based Anomaly Detection