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science, or a related field; strong experience with GIS and spatial data analysis; experience with Python, or a strong willingness to further develop programming skills; an interest in methodological and
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contribution to human wellbeing (e.g. IPBES and SEEA); Strong quantitative skills and ability to work with large (geospatial) data sets. Experience with GIS software and fluency in Python or R is needed
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programming and data analysis tools (e.g., SQL, Python, R, GIS platforms); experience with the management and analysis of human subject data (e.g., from questionnaires, interviews, behavioural experiments, eye
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research papers; present research-in-progress at e.g. workshops/conferences; contribute to spatial analysis and GIS-related courses of the department; follow a 30EC training programme to prepare for your
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modelling, and some experience with linked data standards and knowledge graph tools (e.g., RDF, OWL, SHACL); familiarity with or interest for GIS, cartographic maps, geodata infrastructures and geo-analytical
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, NodeJS. Experience on one or more of the following paradigms would be considered a plus: C++, C#, Qt, Python, REST, TensorFlow, Docker, user interface design. Previous experience in GIS systems would be a