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We are seeking a Postdoctoral Researcher in Geospatial Urban Big Data to support the analysis of urban dynamics and decision-making in territorial planning. The candidate must be proficient in GIS
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). Experience handling diverse data types (tabular, time-series, geospatial, text). Strong mentoring skills and interest in education. Desirable Qualifications: Experience with project-based learning or working
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modern ML toolkits and libraries (e.g., TensorFlow, PyTorch, scikit-learn, pandas, Jupyter). Experience handling diverse data types (tabular, time-series, geospatial, text). Strong mentoring skills and
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-driven inquiry using large-scale datasets (social, geospatial, behavioral) and integrate empirical insights with theoretical models. Mentor students in producing publishable research, prototypes, and
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-making, value trade-offs, and policy implications in complex environments. Support data-driven inquiry using large-scale datasets (social, geospatial, behavioral) and integrate empirical insights with
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for spatio-temporal data. Advanced Python skills and experience with ML frameworks and geospatial tools (e.g., PyTorch/TensorFlow, rasterio/GDAL). Ability to work independently and produce reproducible
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related field. Strong track record in remote-sensing imagery and/or time-series analysis and ML/DL for spatio-temporal data. Advanced Python skills and experience with ML frameworks and geospatial tools
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Geospatial analysis, machine learning, and predictive modelling, Have a good command of programming tools such as R packages, Phyton, and other programming languages Publications in the field Excellent
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spatial distribution of critical topsoil properties in global drylands. Process large-scale geospatial and remote sensing datasets using High Performance Computing (HPC) systems. Conduct data analysis, and
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, Agronomy, modeling, biostatistics, or related field The applicant should have documented knowledges in Geospatial analysis, machine learning, and predictive modelling, Have a good command of programming