399 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" scholarships in United Kingdom
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling
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. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: Do SR techniques improve human face identification accuracy? How do SR-enhanced images affect
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contribute significantly to these growing fields. This PhD position is ideal for candidates interested in the following areas of machine learning: Geometric learning: exploiting the structure of data (e.g
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details can be found at https://www.net-zero-fibe-cdt.eng.cam.ac.uk/ The project is funded in collaboration with Network Rail, the entity responsible for the operation and maintenance of the Great Britain's
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website for more details about our research: https://lewisgroup.org.uk How to apply For informal enquiries, email Jamie at j.e.m.lewis@bham.ac.uk including a copy of your CV. Please apply through
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shortlisted for funding by the NRPDTP. Shortlisted applicants will be interviewed on 30 April 2026. Visit our website for further information on eligibility and how to apply: https
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2026. Visit our website for further information on eligibility and how to apply: https://biodtp.norwichresearchpark.ac.uk/ . Our partners value diverse and inclusive work environments that are positive
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different environments influence behaviour and wellbeing. Advanced analytics, including AI and machine learning, will be used to interpret behavioural and emotional data, enabling real-time insights
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for the following programme: https://study.ed.ac.uk/programmes/postgraduate-research/495-informatics-ipab-robotics-computer-vision-computer-graphics with a start date of 14 September 2026 (home applicants