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circumstances, the doctoral degree can have been completed earlier. Additional requirements: PhD in physical geography, remote sensing, geoinformatics, forest ecology, environmental science, or a closely related
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Position Description The Ashley School of Global Development and the Environment Natural Resources and Environment Postdoctoral Associate The College of Agriculture and Life Sciences (CALS) is a
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approaches. Experience working with global livestock, land-use, climate, remote-sensing. Satellite images, or sustainability indicator datasets. Competence with GIS tools and spatial analysis software
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experience with Elmer/Ice and/or GlaDS is a plus. • Data Processing and Inversion: Process and integrate field observation data from the ERC project (GNSS, seismograms, Sentinel/Landsat remote sensing data
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Homepage https://earth.ecu.edu/ Advertising Department EARTH, ENVIRONMENT & PLANNING, DEPT OF Division Academic Affairs Classification Title Postdoctoral Scholar Competency Level Working Title NOAA ESLR
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postdoctoral research associates. These are 12-month (calendar year), 100% research special appointments located in Lincoln, Nebraska, with remote work negotiable. One postdoc will be working within
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motivated Postdoctoral Researcher to advance smart sensing and AI technologies for sustainable aluminium recycling as part of the Horizon Europe CLEANMAT (Smart Clean Aluminium Material Processing) project
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 1 month ago
Science, remote sensing, oceanography, or equivalent Experience with Mitgcm, satellite data processing, and in-situ data analysis preferred. Understanding of the processes happening at the ice-ocean
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Experience developing software with Python, R, and/or Julia Experience with machine learning and AI algorithms and tooling (e.g. PyTorch) Experience with remote sensing and open-source GIS tools (e.g. Google
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/benefits-overview . Posting Summary Seeking a highly motivated Postdoctoral Associate to lead research working in quantitative ecology, using big datasets (e.g. GBIF, eBird, Movebank), remote sensing data