386 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" PhD positions in United Kingdom
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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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Applicants should apply via the University’s admissions portal (EUCLID) and apply for the following programme: PhD in ICSA with a start date of 1 September 2026. Applicants should state “Memory Optimisation for Distributed ML Systems” in the ‘Research Topic’ section of the application form, and...
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Engineering, Mechatronics, or Robotics, with a heavy emphasis on dynamic system theory, or a closely related discipline. Strong academic background in applied intelligent control techniques, machine 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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from working closely with its team of post-docs, associated researchers and partners (that range from Microsoft Research to the NHS). For this project you should have a strong interest in AI/Machine
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engineering, machine learning, molecular design, and sustainability, helping to create smarter ways of identifying promising sorbents for electrochemical CO2 capture. Over the course of the project
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well as the constructed Brain Research and Imaging Centre (BRIC; https://www.plymouth.ac.uk/research/psychology/brain-research-and-imaging-centre ). For more details of the School’s research activity, please visit our
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for the computer simulation of electronically excited processes in molecules and materials. In the age of net-zero it is more important than ever to obtain a deep, molecular-level understanding of the working
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the supervisor’s complimentary research expertise in this area (https://millerresearchgroup.co.uk & https://www.lovelockresearchgroup.co.uk),[8,9 ] this PhD will involve the design and chemoenzymatic synthesis of a
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records that can systematically inform preparedness, training and future response. As a result, learning from past events is fragmented, inconsistently captured, and insufficiently embedded into emergency