64 big-data-and-machine-learning-phd Fellowship positions at University of Nottingham
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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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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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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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very good working knowledge of statistically packages such as SPSS, AMOS, Stata or R Experience of cleaning, recoding and cataloguing large and complex data sets suitable for time-dependent
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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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properties of vibrational sources in large built-up structures, such as cars or airplanes. We will incorporate data from measurements and implement these sources into large-scale structure-borne sound
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/Fellow who can deliver the research whilst helping to manage project delivery. Candidates must hold an appropriate engineering or science degree level qualification and a PhD (or be about to obtain a PhD
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10 minutes and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre
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, alignment, and characterisation of laser-based instrumentation. • Strong experience with computer programming, both for signal processing and experimental hardware control (e.g., C, C++, Python, MATLAB