565 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at University of Sheffield
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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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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
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Topologically constrained physics-informed machine learning for modelling complex spin textures (S3.5-COM-Ellis) School of Computer Science PhD Research Project Competition Funded Students Worldwide
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Machine Learning-Guided Discovery and Experimental Validation of Novel Antimicrobials Against Pseudomonas aeruginosa (S3.5-MPS-Soukarieh) School of Mathematical and Physical Sciences PhD Research
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between the brain signals of different subjects. The aim of this project is developing new adaptive and machine learning algorithms to successfully decode brain signals across subjects. The prospective
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acids institute (https://sheffield.ac.uk/nucleic-acids) and the centre for Single Molecule biology (https://smash.sites.sheffield.ac.uk/), providing additional expertise. This project will contribute
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neurological and cardiovascular disorders. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying References GONZÁLEZ-SANTANA, A., ESTÉVEZ-HERRERA, J., SEWARD
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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line
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BSM processes. This will involve taking a lead role in developing dedicated software frameworks, including the implementation of machine learning techniques. A long-term attachment (6-12 months) and
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, or equivalent. Please see this link for further information: https://www.sheffield.ac.uk/postgraduate/phd/apply/english-language. Funding Notes Applications for projects from sponsored or self