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fellow to assist with implementing science algorithms for processing imaging spectroscopy data from its raw state (Level 0) through to global gridded data products (Level 3).** The fellow will also have
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of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: Alfalfa is the world’s most important forage legume crop, and its plant genetic resource
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newly established network of experimental silviculture and genetics plots while leveraging existing long-term studies and datasets to meet urgent questions in the near-term. The research fellow will
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300 species. https://www.ars.usda.gov/northeast-area/geneva-ny/plant-genetic-resources-unit-pgru/docs/about-pgru/ Research Project: Participants will have the opportunity to explore genetic variation
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of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: This appointment is part of the Abiotic Stress Laboratory at Grape Genetics Research Unit
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breeding. Learning Objectives: The participant will gain skills in laboratory methodologies, experimental design, horticulture, genetics, data analysis, statistics, and plant pathology. The participant will
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systems. The candidate will be responsible for processing repeat pass inSAR data and implementing efficient data calibration algorithms based on heterogeneous spatial sampling of ground truth points
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of all-sky microwave radiance assimilation algorithm are highly encouraged. Field of Science: Earth Science Advisors: Zhu, Yanqui (301) 614-5844 yanqiu.zhu@nasa.gov Applications with citizens from
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of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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retrieval algorithm development with focus on using the polarimetric signals, the new FIR or sub-mm bands, and/or the ML/AI approach; (3) ML/AI application on system/pattern tracking on satellite images