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the following areas: Data analysis and programming, e.g. Python, R GIS and spatial analysis Data visualisation Language Requirements: Applicants must demonstrate at least B2-level proficiency in the language of
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candidate who has: A PhD in hydrology, environmental engineering, environmental science, geography, ecology, or a related field Strong experience in hydrological modelling Proficiency in R and/or Python
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record in peer-reviewed international journals Experience with remote sensing, LiDAR, and GIS applications Programming skills in Python Background in LiDAR point-cloud analysis and vegetation structure
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(preferably in R, Python, GIS) • Competences in quantitative research methods - ideally knowledge of several of the following aspects of quantitative data analysis: analysis of large/longitudinal datasets
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, or a related field Strong experience in spatial and/or landscape modelling Proficiency in R and/or Python Experience with GIS and remote sensing Ability to work with large and heterogeneous datasets
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and applied statistics, including use of tools such as R, Python, GIS, Git or similar data-science software. Solid experience with community data and biodiversity monitoring. A broad ecological