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Field
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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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, project and program evaluation, and report writing. Data science and Geospatial Analysis skills, including coding (e.g., Python, R), inferential statistics (e.g., MATLAB, STATA), predictive modeling, GIS
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of tools such as R, Python, GIS, Git or similar data-science software. Solid experience with community data and biodiversity monitoring. A broad ecological background, ideally including plants and
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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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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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competitions including creating challenges Building integrated dashboards with any of the following tools: SQL Server, PowerBI, Tableau, Python/Machine Learning, AWS, Azure. Security clearance (current or
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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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comparable field Very good knowledge of quantitative research methods in medicine or health sciences Demonstrable subject-specific programming skills (e.g., R, Python, etc.) Experience with database usage (e.g
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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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sustainability or Basic software engineering knowledge and interest in GIS Programming skills like Java, Python, Docker and knowledge of cloud resources (e.g., GCP, AWS) Analytical thinking and enthusiasm