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Field
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) data sets in R or Python as well as GIS software such as QGIS or ArcGIS Pro. Knowledge of US forest ecosystems and background in analyzing forest structure, stand dynamics, biodiversity, and/or other
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programming and strong quantitative skills. Desirable Demonstrated knowledge of advanced biogeographic, comparative, and phylogenetic methods, quantitative methods in biodiversity studies, GIS in R, and spatial
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, Hydrology, Environmental Science, or a related field. Experience in machine learning or AI applications in hydro-climate studies. Strong background with GIS tools and spatial analysis techniques. Demonstrated
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supervision The following experience will strengthen your application: Advanced coding skills (Python, R, etc.) Expertise in GIS and data visualisation. Experience applying Machine Learning, particularly
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data visualisation and mapping for research communication. • Proficiency with statistical and geospatial software (e.g., SPSS, R, Python for GIS). • At least 3 years of relevant work or research
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impact assessment, or a closely related field. Required Knowledge, Skills, and Abilities Strong analytical and quantitative skills, including statistical programming (e.g., R, Python, or similar
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and oral communication skills Proficiency in data analysis tools (e.g., R, Stata, Python, NVivo, GIS) Experience with interdisciplinary or community-based research is a plus How to apply: Interested
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: Experience with analyzing GPS tracks Good data-handling skills and ability to use R (compulsary) and preferably also Python and/or GIS competently Statistical/causal inference knowledge PhD degree in a related
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degree in Economics (Master of Science degree of advantage) ; Demonstrated experience in programming languages such as Stata, R or Python. Previous knowledge of Dynare, GIS and/or Matlab applications and
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are looking for – Selection Criteria: Essential: Experience in basic GIS skills using QGIS or ARCGIS Demonstrated experience working in scientific report writing Experience working in data analysis using R