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Statistics and AI for Engineering and Smart Manufacturing School of Mathematics and Statistics PhD Research Project Competition Funded Students Worldwide Dr Wei Xing Application Deadline
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Using Multivariate Statistical Surrogate Models of Displacement Cascades To Simulate High-dose Irradiation Damage Department of Materials Science and Engineering PhD Research Project Directly Funded
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Statistics and AI for Engineering and Smart Manufacturing
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Using Multivariate Statistical Surrogate Models of Displacement Cascades To Simulate High-dose Irradiation Damage
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, three major charities and the Office for National Statistics, and works in close partnership with a large network of partners and leading international research teams. We believe that a diverse and
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datasets, to extract meaningful, statistical information about battery microstructure evolution and degradation. By combining the use of state-of-the-art testing facilities within the Sheffield Tomography
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campaign to promote physical activity or encourage recycling) by evaluating whether behaviour or outcomes following the intervention are statistically different from before the intervention or among a
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learning new statistical and computation tools. No prior knowledge in specific methods is required but it is preferable that the student can demonstrate abilities to learn new computational tools
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statistical analysis of quantitative data Strong communication skills Desirable Experience of conducting eye tracking research Experience of using R for data processing and statistical analysis An interest in
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yield stringent constraints on general new physics models. The PhD project will involve heavily data analysis, statistics, advanced analytical classification methods and possibly machine learning. The PhD