536 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" uni jobs at University of Sheffield
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Accessible Tinnitus Notch Noise Therapy via Machine Learning, Acoustic Metamaterials and Additive Manufacturing (with NHS and TinnitusUK) EPSRC Centre for Doctoral Training in Sustainable Sound
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Conrad, N. (2020). Proofreading revisited: Interrogating assumptions about postsecondary student users of proofreading. Journal of English for Academic Purposes, 46, 100871. https://doi.org/10.1016/j/jeap
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Physics based machine learning algorithm to assess the onset of amplitude modulation in wind turbine noise (with TNEI Group) EPSRC Centre for Doctoral Training in Sustainable Sound Futures PhD
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. Visit http://www.sheffield.ac.uk/sgs to learn more. Funding Notes First class or upper second 2(i) in a relevant subject. To formally apply for a PhD, you must complete the University's application form
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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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abilities and experience the breadth 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
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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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Adversarial machine learning - Identification and prevention of cyber-physical attacks on infrastructure (S3.5-MAC-Champneys) School of Mechanical, Aerospace and Civil Engineering PhD Research
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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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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