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good knowledge of experimental research methods and statistics, experience with sta-tistical software (e.g. JASP, R)•Programming skills (e.g. in Matlab, Python/Psychopy and/or R) or willingness
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academic advancement and managerial application. List of crucial references Huang, M.-H., & Rust, R. T. (2018). Artificial Intelligence in Service. Journal of Service Research, 21(2), 155–172. https
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activities – Have postdoctoral experience at Spanish and/or foreign universities or R&D centers other than IBEC. Stays or mobility while providing services to IBEC. – any other contribution that makes it
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science, or a related field. Strong background in quantitative methods and statistical analysis. Experience with computational tools for large-scale data analysis (e.g., Python, R, SQL). Familiarity with
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and scored: A. Knowledge of Matlab, Python, R and/or C++ (advanced level). These will be assessed based on accredited training hours (0.5 points for every 10 hours of training, up to 5 points for each
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Matlab, Python, R and/or C++ (advanced level). These will be assessed based on accredited training hours (0.5 points for every 10 hours of training, up to 5 points for each course) and accredited project
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RedCap. Proficiency in statistical software such as R, SAS, or Stata; experience with data visualization and reproducible workflows (e.g., R Markdown, Git) is desirable. Strong publication record in peer
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strong interest in evolution and genomics, and a basic understanding of R or Python. Entry Requirements: At least UK equivalence Bachelors (Honours) 2:1. English Language requirement (Faculty of Science
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measurement; Measurement of related tracers (e.g., Radon); Programming (e.g., R, Python) for advanced atmospheric time-series analyses, including machine learning; Skills for presenting research at scientific
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, bioinformatics, and statistical modelling in R. You will also gain experience in critical thinking, scientific writing, and presenting your research. Transferable skills for academic and non-academic careers will