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economic studies funded by the UK National Institute for Health and Care Research. Experience of conducting economic evaluations using suitable statistical software (e.g. STATA, R or SAS) is essential
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policy. Previous experience of environmental or public health economics, epidemiology or work on energy efficiency would be an advantage, but is not essential. Proficiency in statistical packages such as R
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-scale job ads datasets, spatial datasets, patents). Conduct data analysis using econometric and statistical tools. Excellent knowledge of R is expected. Good knowledge of Python, experience with modern
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public datasets as well as samples generated through collaborations. Ideal candidates will have strong interests in microbiome-host biology, bioinformatics, or machine learning. Experience with R or Python
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prosthetics. The project will be supervised by Prof. Sarah Cartmell, Prof. Julian Yates, and Dr. Jose R. Aguilar Cosme at the University of Manchester. While prosthetic materials continue to evolve, current
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research assistant) or extended work/study/travel in a different cultural context Experience and understanding of qualitative data analysis Experience conducting statistical analyses in R Funding Notes Each
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) and apply for the following programme: https://postgraduate.degrees.ed.ac.uk/index.php?r=site/view&edition=2025&id=493 with a start date of 01 September 2025 Applicants should state “Real-world quantum
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of statistics and quantitative data analysis, hands-on experience with R or Python strong interest in prototyping commitment to and interest in the design and implementation of Open Science/Open Source practices
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research; (c) A strong foundation in technical, analytical, and research skills, enhancing your career prospects in academia, R&D, and the growing clean energy sector; (d) Opportunities to present your work
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area, have extensive experience in conducting model-based economic evaluations using suitable statistical software (e.g. R or Python) and the ability to work independently, prioritise your own workload