550 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at University of Sheffield
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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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careers. Visit http://www.sheffield.ac.uk/sgs to learn more. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying Funding Notes First class or upper
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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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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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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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evolution of rhizobia in the lab and in plant mesocosms alongside omics technologies such as genomics and transcriptomics and analysis of pre-existing datasets. You will learn techniques such as sterile
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Digitalising populations of structural systems using machine learning (S3.5-MAC-Dardeno) School of Mechanical, Aerospace and Civil Engineering PhD Research Project Competition Funded Students
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will also be considered. References Korsós et al., ApJL 802 L21 (2015) https://iopscience.iop.org/article/10.1088/2041-8205/802/2/L21 Korsós, Chatterjee, Erdélyi, ApJ 857 103 (2018) https
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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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are essential. Experience with a computer algebra system such as Mathematica is an advantage. We are also looking for good written and verbal communication skills. The Gravitation and Cosmology Group at Sheffield