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Field
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(IBES), Brown University seeks a Postdoctoral Researcher and/or Field Technician with experience in wildlife ecology, remote sensing/geospatial analysis, field campaigns, habitat suitability modeling
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-analysis of the relationship of hydraulic conductivity and vegetation cover. Data analysis and publication writing. Using remote sensing to evaluate cover conditions on rangelands. Other duties as required
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of Civil and Environmental Engineering / Chaney Lab: Perform the core of the proposed research activities including processing the remotely sensed LST to compute the spatial statistics, run the HydroBlocks
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of agricultural water use. Specific focus areas include applying AI/ML to analyze remote sensing and sensor data for predicting crop water requirements, advancing irrigation scheduling, and supporting real-time
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, digital twin, geospatial mapping with vehicle and UAV mounted remote sensing systems or robotic systems, crowd simulation, reinforced learning, flood modeling and impact analysis, complex system modeling
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or willing to learn geospatial analysis. Self-motivated Willing to pursue research objectives stated in the projects’ descriptions. Quantitively minded A background in Oceanography, Remote Sensing, Meteorology
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Postdoc "Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Founda...
The large collaborative project ‘3D-ABC’, funded for 3 years by the Helmholtz Foundation Model Initiative, will focus on the development of a Foundation Model combining large remote sensing and field datasets
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
to estuary using satellite remote sensing and data analysis. The specific research focus is flexible, offering the opportunity to develop and pursue new ideas within the broader scope of the project. Minimum
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data. Experience working with remote sensing data. Two years of experience using advanced statistics. Excellence in the field as demonstrated by relevant publications, or a fellowship in quantitative
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data. Experience working with remote sensing data. Two years of experience using advanced statistics. Excellence in the field as demonstrated by relevant publications, or a fellowship in quantitative