71 big-data-and-machine-learning-phd Fellowship positions at University of Nottingham
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generating DNA cytosine modification dysfunction in IPF, and potential targets for therapeutic interference in IPF development. Applicants must be highly motivated and self-driven, with a PhD in bioinformatics
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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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/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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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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proposals for both individual and collaborative projects, utilizing established methodologies and techniques to execute research effectively within the specified area; To analyze data meticulously, interpret
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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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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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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