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will focus on two components: Developing a field-based automated phenotyping platform integrating multi-modal remote sensing datastreams, including hyperspectral reflectance, sun-induced chlorophyll
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sensing and decision-making in poultry processing environments. Learning Objectives: Under the guidance of a mentor, the participant will gain knowledge and experience in: Applying hyperspectral imaging
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portfolio including plant science, soil health, bioinformatics, protecting agricultural against invasive species, natural resources, remote sensing, advanced manufacturing, and the nexus of agriculture and
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degree in one of the relevant fields. Preferred skills: Favorable candidates will ideally possess: A strong sense of motivation, accountability, and a willingness to learn and engage Strong written and
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Research Laboratory is offering a Biosensor Research Fellowship in the Operational Sensing Section at the 711th Human Performance Wing (711 HPW), headquartered at Wright-Patterson Air Force Base in Dayton
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. Under the guidance of a mentor, the fellow will participate in a project that combines both in-situ and remote sensing data to develop novel monitoring techniques to measure within-field variability in
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of Agriculture (USDA), Agricultural Research Service (ARS), Hydrology and Remote Sensing Laboratory. This opportunity is in Beltsville, Maryland. The Agricultural Research Service (ARS) is the U.S. Department
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-automated processing pipeline capable of analyzing high-throughput plant phenotyping and soil-sensing data to extract key phenotypic traits. Advancing crop productivity within sustainable cropping systems
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collaboratively with our team, you will analyze forest inventory data, along with ancillary data including gridded climate data, remotely sensed information, land use, human population and income, global trade, and
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operations, senior scientists within the IC annually pinpoint vital research topics spanning diverse disciplines, from artificial intelligence, quantum computing and sensing, biotechnology, and energy and