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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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, coping mechanisms, and job resources affect these trajectories using discontinuous growth modelling and/or other appropriate statistical analyses. Additionally, the student will conduct a qualitative
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aptitude for research design and statistics and will have a background in psychology or a related discipline. They will be supervised by Dr Sam Farley, Dr Nicola Thomas, and Professor Jeremy Dawson from
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success in the German and/or EU market context. The successful applicant must have strong quantitative, statistical, and analytical skills. Demonstrated knowledge of Python and Machine Learning techniques
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Statistics and AI for Engineering and Smart Manufacturing
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, with a dedication to supporting high-quality work. Strong academic background with a degree in computer science, statistics, physics, engineering, mathematics, or related fields. Proficient in Python
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and enthusiastic about doing research in AI for healthcare and a commitment to supporting high quality research. Have a good first degree in computer science, statistics, physics, engineering, or any
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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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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