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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 1 month ago
information (in situ and remotely-sensed observations as well as climate and weather model output) to enhance decision support across a range of impact sectors and applications (in particular related
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smart buildings. At CMVS, the focus is on hyperlocal computing, distributed sensing, and scene reconstruction, building synergies with our healthcare sensorization expertise. Your responsibilities include
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research on new models integrating terrestrial plant biodiversity, ecosystem productivity, hyperspectral remote sensing and airborne LiDAR to test prominent hypothesis of the effect of tree diversity
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the field and laboratory, and proficiency in DNA extraction, sequencing and related data analysis. The project includes aspects of entomology and LiDAR remote sensing, giving the Postdoctoral Researcher
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findings regularly. Prototype algorithms, validate outputs, and document methods clearly Collaborate asynchronously with an international team, present findings regularly Experience with remote sensing
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detection (vision, force, voice), contribute to real-time control software and remote monitoring interface development, and oversee data collection during clinical user trials. They will work closely with a
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developing methods/tools that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning of continental surfaces and their interaction with climate and
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for calibrating remote sensing instruments and validating national and regional aerial biomass maps. The One Forest Vision initiative (OFVi project, https://www.oneforestvision.org/eng ) has enabled the creation
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detection (vision, force, voice), contribute to real-time control software and remote monitoring interface development, and oversee data collection during clinical user trials. They will work closely with a
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of programming or scripting languages such as Python, Fortran, R or others. Experience in remote sensing data analysis and geographic information systems. Experience in machine learning motivated algorithms and