482 data-"https:"-"https:"-"https:"-"https:"-"LaTIM---Brest" PhD positions in United Kingdom
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PhD studentship in Computational Chemistry – Training force fields for computer-aided drug design with machine learning. Award Summary 100% fees covered, and a minimum tax-free annual living
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holding a master’s degree, will be considered on an individual basis. Selection process Please see our website for further information Website for additional job details https://www.swansea.ac.uk
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. Seaborn's research. Further information on the PhD in Computer Science programme can be found at: https://www.postgraduate.study.cam.ac.uk/courses/directory/cscspdpcs/apply All applications should be made
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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This PhD project aims to transform paediatric healthcare by addressing critical data and research gaps through advanced artificial intelligence (AI). Despite its importance, paediatric healthcare
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manufacturing sectors, from SMEs to large global manufacturers. For details, visit the MTC website . Entry requirements: A 1st or high 2:1 degree in computer science, manufacturing/industrial engineering, data
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Project advert Modern artificial intelligence (AI) increasingly relies on combining multiple sources of information, such as sound, motion, images, and sensor data, to achieve robust and intelligent
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skills, which will be required to lead the development of automated data analysis and modelling. The student will also undertake a research secondment to coral reef monitoring sites at NEOM for three
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. Information session We are inviting you to attend an online information session about LUMS PhD programmes on 13th January 2026, 12:00-13:30 (GMT). Prospective students will obtain information about our PhD
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap