561 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" uni jobs at University of Sheffield
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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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contact persons. For further Information, please email k.lohwasser@sheffield.ac.uk and T.Vickey@sheffield.ac.uk or look at the University’s website: https://www.sheffield.ac.uk/postgraduate/phd. Further
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accepted all year round Details The advent of easily accessible high performance computers or computer clusters and numerical techniques such as finite element methods (FEM) facilitates the highly accurate
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, November, 427–435. https://doi.org/10.1201/9781003558859-47 [2] Rui, S., Xu, H., Teng, L., Xi, C., Sun, X., Zhang, H., & Shen, K. (2023). A Framework for Mooring and Anchor Design in Sand Considering Seabed
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-to-phenotype mapping, and interactions with landscape processes. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying Funding Notes Self or externally funded
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training opportunities designed to support your career development, including communication and technology skills that are essential in academia, and industry. Visit http://www.sheffield.ac.uk/sgs to learn
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the workshop but will also spend time in laboratories repairing or installing equipment. We are a modern workshop using both CNC and manual machines to produce quality components and using CAD software
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protein machinery regulating vesicle docking, priming and fusion will be investigated. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying References
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to produce similar ‘carbon-capture’ plants using gene-editing technology. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying Funding Notes Open to Self
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intelligent sensing, followed by detection of the important events.In the light of autonomous decision making, the project aims at developing machine learning algorithms for knowledge extraction from data