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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 16 hours ago
the western United States. The project will provide hands-on experience in satellite remote sensing, geospatial analysis, wildfire science, and multi-sensor Earth observation, complementing the participant’s
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 22 days ago
inform representations and encoder adaptations. This activity will provide hands-on experience in making three-dimensional vegetation structure accessible within data-driven geospatial modeling processes
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of large-scale geospatial and time-series datasets. The candidate will develop and evaluate multimodal AI models to characterize vegetation and land-surface dynamics and quantify ecosystem responses and
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October 2026 Apply now Do you want to use artificial intelligence, geospatial data science, and urban analytics to create healthier and more equitable cities? Are you excited about developing innovative AI
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biodiversity datasets with the integration of diverse geospatial and remote sensing data sources to quantify environmental stressors and their impacts on ecosystems. This position offers a unique opportunity to
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start date. Preferred Qualifications: Research experience in computer vision, NLP, geospatial data systems, or high-performance computing. Brief Description of Duties: The Postdoctoral Associate will
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technologies, digital soil mapping/pedometrics, proximal/remote sensing, and geospatial modeling. The ideal candidate will work and collaborate closely within a research team at Texas A&M AgriLife and USDA-ARS
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make a difference in the world! Position Information Texas A&M AgriLife Research at Temple is seeking a highly motivated scientist with expertise in crop modeling, remote sensing, and geospatial
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datasets and remote sensing products (e.g., satellite-derived indices, geospatial data analysis) is highly desirable. The selected candidate will also provide support (30%) to a second project focusing of
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) Evaluate the implications of these associations for extraction processes; and 3) Assess the critical mineral resource potential of unconventional wastes through geospatial and statistical analysis of supply