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) Documented record of advanced quantitative methods skills in R and Python, specifically Experience with GIS and spatial data analysis Experience with natural language processing or text-as-data approaches
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R and Python, specifically Experience with GIS and spatial data analysis Experience with natural language processing or text-as-data approaches Familiarity with large-scale survey data, conflict and
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dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles
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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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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 advantage Knowledge
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background in statistics is required, as well as experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate
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: Required qualifications: Experience with data analysis and familiarity with statistical software (e.g., R, Stata) The applicant must be fluent in oral and written English, see documentation requirements
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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