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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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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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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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PhD (or near completion) in a relevant area such as Psychology, Mental Health, or Social Sciences. Experience in qualitative and/or mixed methods research. A demonstrable commitment to co-production and
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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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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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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
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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