69 big-data-and-machine-learning-phd Fellowship research jobs at University of Nottingham in Uk
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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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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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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
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of sterile and infected single and co-cultures of immune and stromal cells, and correlative data analysis including surface characterisation of biomaterials. Candidates must have a PhD submitted (or close
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. You will be responsible for supporting the delivery of a large National Institute for Health Research (NIHR) funded programme of research into eczema online trials, led in partnership with citizen
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experiments and test candidate therapeutics on leukaemic stem cells isolated from primary patient samples. You will be responsible for carrying out laboratory research, data analysis and presentation of results