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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 interprets cancer surveillance, population, geographic, environmental, and health services catchment area data using appropriate data management, statistical, GIS, and other programming software
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guidance to support staff and/or student employees. Must be proficient in the use of python, JavaScript, CSS, and HTML; PostgreSQL, MySQL, and SQL oracle; Linux Red Hat and Ubuntu ****The final salary
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, AMOS, SAS (Statistical Analysis Software), Microsoft Excel (advanced modeling), Python, R Qualitative Analysis Tools: NVivo Geographic & Mapping Tools: ArcGIS, QGIS (Quantum GIS), Google Earth Pro
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contribution to human wellbeing (e.g. IPBES and SEEA); Strong quantitative skills and ability to work with large (geospatial) data sets. Experience with GIS software and fluency in Python or R is needed
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comparable field Very good knowledge of quantitative research methods in medicine or health sciences Demonstrable subject-specific programming skills (e.g., R, Python, etc.) Experience with database usage (e.g
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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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competitions including creating challenges Building integrated dashboards with any of the following tools: SQL Server, PowerBI, Tableau, Python/Machine Learning, AWS, Azure. Security clearance (current or
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of tools such as R, Python, GIS, Git or similar data-science software. Solid experience with community data and biodiversity monitoring. A broad ecological background, ideally including plants and
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, project and program evaluation, and report writing. Data science and Geospatial Analysis skills, including coding (e.g., Python, R), inferential statistics (e.g., MATLAB, STATA), predictive modeling, GIS