566 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" positions at University of Sheffield
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project will involve data analysis, advanced statistical methods and the potential to develop pioneering reconstruction and calibration techniques involving machine learning. The PhD will prepare equally
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University to break the Guinness World Record for the highest-resolution microscope ever created. You can read about it in Scientific American: https://www.scientificamerican.com/article/see-the-highest
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Self funded or externally sponsored students only. Intakes are usually October and March annually. NB The University has some scholarships under competition each year. More details can be found - https
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. How to apply: Please complete a University Postgraduate Research Application form available here: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying. Please clearly state the prospective main
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Machine Learning-Guided Discovery and Experimental Validation of Novel Antimicrobials Against Pseudomonas aeruginosa (S3.5-MPS-Soukarieh)
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. The research will integrate advanced full-field imaging techniques, including X-ray computed tomography, neutron tomography, and related methods, with modern machine-learning approaches such as sparse regression
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(IELTS) average of 6.5 or above with at least 6.0 in each component, or equivalent. Please see this link for further information: https://www.sheffield.ac.uk/postgraduate/phd/apply/english-language. Please
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Vision concepts, including image processing, machine learning for visual inspection, and AI, within a manufacturing environment. Your work may also involve developing novel demonstrators for Computer
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@sheffield.ac.uk and T.Vickey@sheffield.ac.uk or look at the University’s website: https://www.sheffield.ac.uk/postgraduate/phd. Further Information on the Particle Physics group in Sheffield and our projects can
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project will develop a physics-informed digital twin for offshore wind foundations, combining ultrasonic guided wave monitoring, high-fidelity finite element simulations, Bayesian inference, and machine