552 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" positions at University of Sheffield
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of materials (e.g., DSC, mechanical testing). Excellent experimental, analytical, and communication skills. How to Apply Please submit your CV, academic transcripts, via the portal at https://sheffield.ac.uk
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. This PhD project will build directly on this work by using ideas from machine learning—originally developed to study the movement of larger organisms—to understand how bacteria process information in
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For further reading see e.g., De Pontieu, Erdelyi and James, Nature 430, pages 536–539 (2004) https://www.nature.com/articles/nature02749 Dey et al., Nature Physics, 18, pages 595-600 (2022) https
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Application form available here: http://www.shef.ac.uk/postgraduate/research/apply Please clearly state the prospective main supervisor in the respective box and select School of Clinical Medicine as the
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Fully-funded EPSRC CDT in Machining, Assembly and Digital Engineering for Manufacturing (MADE4Manufacturing) School of Mechanical, Aerospace and Civil Engineering EPSRC Centre for Doctoral Training
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: https://www.sheffield.ac.uk/postgraduate/phd/apply/english-language. How to apply: Please see this link for information on how to apply: https://www.sheffield.ac.uk/cbe/postgraduate/phd/how-apply. Please
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of application review and, where applicable, interview. Eligibility and application guidance can be found here: https://slt-cdt.sheffield.ac.uk/apply For an informal discussion about your application
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, increased carbon dioxide, rainfall and snow regime change and how these impact the biodiversity of ecosystems, and the capacity of ecosystems to cycle carbon and nutrients (https://sites.google.com/a
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at the University of Sheffield. There will be many opportunities to collaborate with ongoing work in the lab. For more details see http://www.alisonewright.co.uk. Applicants are strongly encouraged to contact Dr
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, the project proposes to also use machine learning techniques to learn parts of the prior and penalty structure from data in an interpretable way. Examples include mapping liquidity and volatility features to a