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habitat or alternative food sources. Be familiar with recent developments on the introduction and spread of two spot cotton leaf hoppers in cotton crops. Have experience with methods for data analysis and
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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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, 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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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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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