65 big-data-and-machine-learning-phd Fellowship positions at University of Nottingham
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to modern slavery in conflict settings. This attempt requires a large, interdisciplinary team working within a cross-cutting framework to connect vast amounts of data and answer many fundamental questions
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the University’s international reputation as a hub for cutting-edge research. Candidates must have a PhD degree in Power Electronics, Machines, and Drives or a closely related field, with a proven track record in
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to modern slavery in conflict settings. This attempt requires a large, interdisciplinary team working within a cross-cutting framework to connect vast amounts of data and answer many fundamental questions
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quantitative and digital methods, such as descriptive/inferential statistics, data modelling, machine learning (ML), experimental prototyping and technology ideation. A significant degree of autonomy is required
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the lead on, plan, develop and conduct individual and/or collaborative research objectives, projects and proposals either as an individual or as part of a broader programme. - To acquire, analyse
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set-up, and data collection and analysis. - Have the ability to analyse and interpret data using appropriate statistical packages (e.g., conducting linear mixed effects models in R). - Have experience
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programme. To acquire, analyse, interpret and evaluate research findings/data using approaches, techniques, models and methods selected or developed for the purpose. To establish a national reputation and
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(particularly under extreme conditions), and/or the use of machine learning for solid mechanics/stress analysis problems are encouraged to apply. The job description presented here is deliberately broad due
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/Fellow who can deliver the research whilst helping to manage project delivery. Candidates must hold an appropriate social science degree level qualification and a PhD (or be about to obtain a PhD, which
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and big data mining. The research fellow will take a leading role in an EU-Africa research project, collaborating with Research Organisations, Academia, and Industry in South Africa, Switzerland, France