329 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" PhD scholarships in United Kingdom
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, particularly MRI, medical physics or computational data analysis (Python/R/MATLAB, machine learning, or bioinformatics) is highly desirable. Interested candidates should send a CV to michael.chappell
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, or other related academic discipline. Good programming skills (preferably Python). Background/work experience in Cyber Security, Machine Learning, and Finance would be highly beneficial. How to apply
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CFD, thermofluids and machine learning. Experience in Python (or another language), machine learning frameworks, or CFD tools such as OpenFOAM is beneficial but not required. Applicants should hold (or
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diagnosis and prognosis technologies, and, consequently, improve maintenance decision making. Currently, machine learning exists as the most promising technologies of big data analytics in industrial problems
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within the climate change domain. The techniques are based on statistical and computational approaches, including machine learning algorithms. The project aims first to contribute to the prevention of fake
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This exciting opportunity is based within the Power Electronics and Machines Control Research Institute at Faculty of Engineering which conducts cutting edge research into power electronics
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(csrankings.org) Home to world-leading research in computer vision, AI, multimodal learning, and robotics You will join a vibrant and tightly knit team of more than 10 other researchers working on a range of
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of lightweight, logic-based machine learning approaches. In addition, agents must support collective decision-making to achieve system-wide optimisation rather than isolated, local improvements. Finally
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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
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health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities