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modelling and statistical and GIS software (R, QGIS/ArcGIS, Python). - Excellent scientific writing and communication skills in English and Spanish. Specific Requirements • Doctorado en Programas de
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are looking for an enthusiastic individual with a degree in a quantitative discipline. Experience of geospatial analysis (with GIS) is essential and programming with code (e.g. R, Python) would be advantageous
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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Additional Information Eligibility criteria Technical skills: proficiency at ecological modelling, use of the Unix/Linux environment, proficiency at oceanographic data repositories and GIS tools, good
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Wetsus - European centre of excellence for sustainable water technology | Netherlands | about 1 month ago
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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) Documented record of advanced quantitative methods skills in R and Python, specifically Experience with GIS and spatial data analysis Experience with natural language processing or text-as-data approaches
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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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, 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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· Data handling, processing and modelling · Familiarity with GIS tools (e.g., ArcGIS, QGIS is a plus · Proficiency in Python scripting for data analysis and automation is a plus
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topographic indices as environmental variables for mapping, and satellite data for weather. The doctoral student will be part of a broad research group with expertise in GIS, AI, soil science, forest ecology