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mentoring of members of our research network, as well as outreach activities, all generally related to your research topic though not exclusively. You are encouraged to visit the ESA website: https
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, Geospatial Science, Data Science, Computer Engineering, or a closely related field, with an emphasis on machine learning, AI, remote sensing, computer vision, or interdisciplinary data science applications
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preprocessing; Integration of geospatial and soil data into databases. Data processing and analysis: Application of geoprocessing and spatial analysis techniques; Development and calibration of predictive models
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05.11.2025, Wissenschaftliches Personal The professorship Big Geospatial Data Management is seeking to fill a research associate position (doctoral candidate or postdoc) to support research
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to the geospatial data processing for the automated creation of digital models. Preparation of associated scientific and technical documentation, including articles, reports, and conference papers Where to apply
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 23 days ago
, multivariate, and longitudinal data analysis using licensure data and large secondary population data sources. * Perform geospatial analysis including translating practice addresses to maps and other data
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/visualisation platform to integrate climate-health evidence from community-driven data, secondary data synthesis and cross-sectoral workshops. The role requires a strong foundation in geospatial data and a
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and apply advanced analytical frameworks--including geospatial statistics, machine learning tools, air quality modeling, and source apportionment techniques--to interpret air pollution observations and
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or Geospatial Intelligence courses. The student will work under the direct supervision of a faculty member. The IESA Student Assistant will support faculty as assigned. This may include proctoring labs and lab
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Description Implement and validate machine learning models and statistical algorithms for data imputation, anomaly detection and uncertainty management in geospatial environments. Collaborate in the preparation