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explore the epidemiology of enteric illnesses associated with animal contact and learn how multistate outbreak investigations are conducted through collaboration among federal, state, and local officials
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-breeding innovation through artificial intelligence and data-driven approaches. You will help develop machine-learning tools that enhance decision-making for weed management across the U.S. Cornbelt and key
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. Learning Objectives: You will learn many innovative techniques (electrospinning and microencapsulation) related to the chemical modification of cotton and other natural fibers, nanoparticle synthesis and
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learning opportunity focused on public health communications within the Outbreak Response and Prevention Branch. The project provides an educational opportunity to explore how communication strategies
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, such as R, Python, and statistics, and to learn collaboration and leadership skills through workshop and group experience. USDA-ARS Mentor: If you have questions about the nature of the research, please
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, such as R, Python, and statistics, and to learn collaboration and leadership skills through workshop and group experience. USDA-ARS Mentor: If you have questions about the nature of the research, please
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are to enhance barley and oat productivity, quality, and stress resilience by combing traditional, molecular, and genomics methods. You will collaborate with other scientists in the unit and other institutes
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population-based datasets, such as the Pregnancy Risk Assessment Monitoring System (PRAMS), National Survey of Children’s Health (NSCH), and related sources. Collaborate with clinical-site partners to learn
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understand the burden of diabetes and inform public health strategies to improve prevention, treatment, and health outcomes. Learning Objectives: Through this training opportunity, you will have the
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in fast-paced collaborative environment (e.g., MS Teams and SharePoint), practice responsible and appropriate use of AI tools, and have a desire to learn about CDC responses. Have some experience in