223 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions in United Kingdom
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Requirements We are seeking enthusiastic, curious, and motivated individuals with: A strong academic background in computer science, artificial intelligence, machine learning, data science, engineering, or a
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Although large numbers of adults attend Welsh for Adults classes nationally, statistics from 2019–2024 show that only around 26% progress beyond Entry level (CEFR A1; National Centre for Learning
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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) Start date: September 2026 Project Title: HEALS: Heat, Health, and Learning: Co-Designing Climate-Resilient Strategies for Primary Schools in Oxfordshire Director of Studies: Prof Rajat Gupta Supervisors
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results is desirable. To be considered for this PhD, please follow the instructions here: https://www.centre-ub.org/studentships/application-process/ Application deadline: February 17 2026 Interviews
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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
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, release kinetics under biologically relevant triggers. The successful candidate will work at the interface of organic synthesis, chemical biology, and machine learning to guide linker design and optimise
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nationally, statistics from 2019–2024 show that only around 26% progress beyond Entry level (CEFR A1; National Centre for Learning Welsh, 2025). Increasing these progression rates is a key aim of the Welsh
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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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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer