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modeling and risk assessment. This role requires expertise in ML model development, geospatial analysis, and environmental data processing. Responsibilities Design and optimize machine learning models (LSTM
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 1 month ago
the combination of socioeconomic data and geospatial information. Experience with the calibration and deployment of low-cost sensors is preferred. Occasional travel may be necessary. Field of Science: Earth
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spatial analysis and vulnerability mapping for flood-prone regions. Utilize remote sensing and geospatial tools to analyze flood exposure and mitigation strategies. Support the ClimateIQ project by
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. The post-doctoral research associate will be a key member of the Center of Geospatial Intelligence and Environmental Security research team and will be involved in ecological and agroecosystem change
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following topics: in situ sensor installation and flood monitoring, GIS & geospatial big data, AI/ML and data science approaches for hydrologic predictions, risk analysis. Experience in working with big data
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qualifications: Experience creating informative web-based data visualization, especially with geospatial data (e.g. maps). Successful candidates will be expected to lead and collaborate on research projects full
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learning applied to geospatial data Experience with Amazon Web Services or other cloud-based computing platforms Special Instructions to Applicants: For full consideration, applications must be submitted
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hydrologic connectivity metrics. Furthermore, the qualified candidate must possess advanced skills in geocoding, GIS, raster analysis/processing, and the management of large geospatial datasets. Familiarity
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). This position is funded by a collaborative project funded by the Taylor Geospatial Institute (https://taylorgeospatial.org/ ). The title of the project is: "Rethinking Multimodal Localization Systems at Scale in
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programming language (e.g., Python, MATLAB, R), proficiency in GIS or other geospatial software, preferably field work experience for data collection (survey and damage assessment), and an interest