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climate. Observational work would include data from GRACE, SMAP, GPM or in-situ stations. Model diagnosis and analysis can include CLM, VIC, CLSM, and LIS frameworks including GLDAS and NLDAS. Model
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at the speed of commerce under real-world conditions. The participant will collaborate with a research team to explore best practices in experimental design, hypothesis testing, and data analysis for assessing
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, data analysis, and the application of AI/ML techniques in agricultural research. You will also gain a holistic understanding of the entire research data lifecycle, from experimental design and data
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of Agriculture (USDA), Animal Plant Health Inspection Service (APHIS), Veterinary Services, Center for Epidemiology & Animal Health (CEAH) Domestic Animal Health and Analysis Unit (DAHA) examines all aspects
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and incorporation into a clinical diagnostic lab under ISO-1705 procedures. The fellow will learn and contribute to the experimental design, data analysis and troubleshooting. The fellow will present
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and management practices. This opportunity will provide experience measuring the chemical properties of soil, including pH, electrical conductivity, and elemental analysis, and provide experience
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(e.g., enhancers, promoters) in cattle. Customize bioinformatics pipelines for automated processing and analysis of short- and long-read sequencing data. Apply computational approaches to detect genetic
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. Research Project: Joining a team of landscape and fire ecologists to learn about and support geospatial analysis of fire mitigation implementation in the highly fire prone lands of Kona and Kohala on Hawaii
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. This fellowship offers a unique opportunity to be at the forefront of groundwater technology, gaining experience on projects ranging from groundwater sampling and geophysical imaging in the field, analysis
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for combat trauma, directed energy exposure, extreme environmental exposure, and/or toxicant exposure. You will participate in and learn to perform data collection and analysis pertaining to testing toxicants