583 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" positions at University of Sheffield
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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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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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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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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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collaboration with Special Melted Products (https://specialmeltedproducts.com/) using the unique Royce metals processing capabilities in Sheffield (https://sheffield.ac.uk/royce-institute), that range from alloy
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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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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
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academia, industry and many related careers. Visit http://www.sheffield.ac.uk/sgs to learn more. We are a welcoming, international lab group, with current and past students from China, USA, Thailand, South
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Effective and Efficient Visual Presentation of Machine Learning Outputs Derived from High-Dimensional Data to Clinicians (S3.5-SMP-Alix) School of Medicine and Population Health PhD Research Project