515 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" uni jobs at University of Sheffield
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the third Higgs boson decays to two tau leptons, or another highly sensitive combination. The student will gain expertise in machine learning techniques for signal-background discrimination and will
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Robust machine learning using information theoretic approaches for damage detection in complex machines (C3.5-ELE-Esnaola) School of Electrical and Electronic Engineering PhD Research Project
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accepted all year round Details Project description: Morphogenesis—the process by which tissues acquire their shape—is central to the development and function of all multicellular life. It is increasingly
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of synchronised states using analytical and statistical techniques. Funding Notes This project is for self-funded or externally funded students only. References 1. Synchronisation of rotating turbulent (https://www
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application form using the following link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying References https://sheffield.ac.uk/biosciences/people/academic-staff/claire-turner https://sheffield.ac.uk
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of technologies that are used in academia, industry and many related careers. Visit http://www.sheffield.ac.uk/sgs to learn more. Please apply for this project using this link: https://www.sheffield.ac.uk
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candidates for this project should have a strong background in Applied Mathematics, Engineering, Physics or other related disciplines. Full details of how to apply can be found at the following link: https
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this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying Funding Notes Self and externally funded students only References M P Williamson, 'Autocatalytic selection as a driver for the origin
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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 be found here
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AI-based diagnostics for fleet-based condition monitoring of electric vehicle motors using machine learning frameworks (S3.5-ELE-Panagiotou) School of Electrical and Electronic Engineering PhD