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and weaknesses for end-users. Help develop new or improve existing soil moisture estimates using NISAR and other datasets utilizing artificial intelligence (AI) and machine learning. The outcome from
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agricultural pest systems is highly desirable. Learning Objectives: The overall research goal of the group is to develop new pest management strategies that can augment and enhance current approaches. As such
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supply. The fellow's research supports the mission and goals of ARS National Program 108, Food Safety (100%). The candidate will be a part of development of sustainable technologies that solve
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the development and evaluation of cropping systems that include alfalfa and other perennial crops that are designed to improve soil health, increase productivity and efficiency, and build resilience. This project
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affect oyster phenotypes targeted for improvement. The fellow will also gain experience using advanced computational methods to develop tools that can accurately predict desirable phenotypes. With
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agricultural discoveries through scientific excellence. Research Project: The overall goal of this engineering project is to develop nondestructive sensing-based tools and techniques to reduce food safety risks
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biodefense, biosecurity, or international trade implications. They will collaborate with ARS scientists to develop innovative approaches to describe, identify, and detect microbes found in crop and/or weed
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both local and regional land managers to share results. The fellow will also be able to travel to national or regional conferences to disseminate findings and develop professionally. Possible independent
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these parasites as well as developing rapid methods of parasite detection and drug-resistant parasite strains. This project seeks to compile the genomic sequence of Eimeria, which are protozoa that cause
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positions across the intelligence community, defense sector, and national laboratories. Elite Professional Network: Develop career-defining connections with decision-makers and technical leaders across the 18