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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 17 hours ago
, Landsat, NASA products), and/or geospatial analysis is highly desirable. Familiarity with fire behavior modeling, uncertainty quantification, or explainable AI methods is a plus. Candidates should
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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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, representation learning) Spatiotemporal modeling or geospatial/temporal data analysis Medium-to-Large-scale foundation models pretraining/fine-tuning paradigms Strong programming skills in Python and experience
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Qualifications: PhD with substantial expertise in data science, geospatial techniques, and statistical/causal inference Required Application Materials: CV 1-page cover letter describing research background and
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designing and conducting interviews and surveys, managing large secondary datasets, and building and managing geospatial datasets. Minimum Requirements for the rank of Postdoctoral Scholar: • Ph.D. in a field
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• Enhancing and deploying computational platforms such as Cornell TEAM-Cities, CATChain, uTECH, etc. • Working with geospatial and mobility datasets (GPS trajectories, transit feeds, sensor data, demographic
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sensing, econometrics, land surface modeling, geospatial statistics. o Demonstrated ability to conduct independent research and publish high-quality work in peer-reviewed journals. o Excellent written and
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | about 17 hours ago
atmospheric science, physics, and computer science. Experience in analyzing satellite data and geospatial data are desired. Skills in AI, machine learning, deep learning, keras, Pytorch are preferred. A proven
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pipelines and visualization dashboards to communicate results effectively. Familiarity with geospatial data analysis and methods for extracting insights from unstructured data. Job Family Postdoctoral Job
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related field • Strong quantitative background (e.g. ecological theory and mathematical modeling, hierarchical statistical modeling, machine learning, remote sensing, geospatial statistics) • Demonstrated