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sequencing, qRT-PCR, western blotting, bioinformatics, ELISA, cell culture, statistics, and literature reviews. A working knowledge of these techniques is therefore desirable. We will compare subtypes, detect
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performance and green innovation. It also explores how these effects change when combined with environmental regulations and innovation incentives. The project will employ statistical analysis and econometric
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. The researcher will be an integral part of an interdisciplinary and international team of researchers covering a broad range of topics including statistical physics, condensed-matter theory, computational physics
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Statistics this year. The successful candidate will enjoy many benefits including 30 days annual leave, all bank holidays and additional university closure days, discounted membership to the state-of-the-art
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Sciences currently runs two degree programmes, which lead successful graduates to University of Nottingham degrees in BSc Honours Mathematics with Applied Mathematics and BSc Honours Statistics. Some of our
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occurrence, aetiology, outcomes, and real-world impact. The student will be supported by a supervisory team including Professors in hepatology and epidemiology, and experts in computational statistics and
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successful candidate will: Have extensive experience with qualitative research including study design, data collection, and data analysis. Have high analytical experience to analyse and interpret statistical
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for the treatment of mental health conditions in older adults. The appointed candidate will be responsible for managing the CPRD dataset, conducting statistical analyses in accordance with the research protocol
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activity (with a choice of either EEG or the newly developed OPM-MEG technique). In addition, you will be trained to statistically analyse your data with “off the shelf” (e.g. SPSS) and customisable software
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changes in tinnitus impact. This project will require large scale data collection across multiple settings and platforms, and interrogation of the data using a range of advanced statistical techniques