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microbiology, or environmental microbiology. Strong programming/computing skills (e.g., Python and/or R), Unix/Linux command line, and good practices with Git and reproducible research. Experience using
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modelling, preferably in R Fluent oral and written communication skills in English. Relevant and significant scientific publications in respected journals, at the level of the career status of the applicant
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analysis is a requirement Experience in using relevant software to perform complex tasks, e.g. R, ArcGIS, and Python is a requirement Experience in the mapping and modelling of ecosystem services is an
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CT core scanning, as well as grain size analysis) is a requirement. Experience with (geostatistical) data analysis approaches (at least Excel and ArcGIS, but preferably also R and Grapher or similar
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relevant programming languages (e.g., Python, MATLAB, R) is a requirement. Familiarity with downscaling and bias correction of climate data (e.g., from CMIP/PMIP) is an advantage. Experience with
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science, is a requirement Applicants must possess strong skills in the management and analysis of ecological or biodiversity data using R. Experience (for example, a master’s project or internship) working
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., Python, R, bash). At least one publication in an international peer-reviewed journal of an end-to-end software developed by the candidate Documented experience with Nextflow or Snakemake. Documented
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analysis of ecological or biodiversity data using R. Experience (for example, a master’s project or internship) working with plant, vegetation, or alpine ecology is a requirement. Fieldwork experience and
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(geostatistical) data analysis approaches (at least Excel and ArcGIS, but preferably also R and Grapher or similar) is a requirement Strong skills in statistical analysis and the handling of large spatiotemporal
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. Proficiency in relevant programming languages (e.g., Python, MATLAB, R) is a requirement. Familiarity with downscaling and bias correction of climate data (e.g., from CMIP/PMIP) is an advantage. Experience with