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for the materiality of the built environment in defined regions, based on MFA and supported by BIM, GIS, IoT and AI technologies. Map existing anthropogenic material stocks and their dynamics and simulate circularity
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for the materiality of the built environment in defined regions, based on MFA and supported by BIM, GIS, IoT and AI technologies. Map existing anthropogenic material stocks and their dynamics and simulate circularity
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related field Demonstrated experience in geospatial analysis (GIS) and proven skills in hydrogeological or hydrological modeling Proficiency in programming (e.g., Python) Ability to handle large datasets
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and AI algorithms Solid programming skills in Python and familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) Experience working with geospatial data (e.g., geopandas
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of coastal and marine monitoring data Experience in numerical model data extraction with Python and data analysis in R as well as experience in spatial data analysis with geo-information systems (GIS