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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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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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production, agriculture broadly, and/or smart technologies is desirable. • Experience in modelling biological or agricultural systems, with strong programming skills (R, Python, or Matlab