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data, GIS, and environmental modeling. Familiarity with programming languages such as Python, Julia, R, C++, or MATLAB is considered a strong asset. Experience with fieldwork or working with soil
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experience with knowledge graph standards (e.g., RDF, OWL, SHACL); familiarity with GIS, geodata infrastructures and geo-analytical workflows some experience with AI and machine learning methods to label texts
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remote sensing/climate data. You have programming skills in Python and/or R; you are familiar with reproducible coding and automated geospatial data analysis. You have excellent scientific writing and
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. You have good programming skills in Python and/or R; you are familiar with reproducible coding and automated (geospatial) data analysis. You have excellent scientific writing and communication skills in
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, energy-related datasets. Proficiency in Python, MATLAB, and/or Julia for modeling, simulation, and data analysis. Familiarity with GIS tools (e.g. QGIS), time-series databases (e.g. InfluxDB), and version
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remote sensing/climate data. You have programming skills in Python and/or R; you are familiar with reproducible coding and automated geospatial data analysis. You have excellent scientific writing and
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. You have good programming skills in Python and/or R; you are familiar with reproducible coding and automated (geospatial) data analysis. You have excellent scientific writing and communication skills in