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, performing standardized analyses or running laboratory equipment to analyze chemical constituents of soil, plant and water samples. Learning objectives: During this opportunity, under the guidance of a mentor
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quality and consumer satisfaction. You will also apply statistical and machine-learning tools to explore how physical and chemical fiber parameters relate to dye uptake behavior, dyebath exhaustion, color
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, Training, and Expertise Branch to engage in and learn from a project supporting training programs for new and experienced DRSC inspectors and auditors within FSAP, IPP, and NAC. Learning Objectives: During
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emerging technologies, transportation data, policy, research and all modes of transportation across the Department. As a Fellow, you will learn to facilitate the transformation of our transportation system
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reports/visualizations and presentations, and collaborating with multidisciplinary teams. Learning Objectives: You will train with CDC’s Center for Forecasting and Outbreak Analytics, gaining hands
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, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural
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expensive and dangerous health threats, and responds when these arise. Research Project: This project will be across teams in the branch to provide an opportunity to learn about the needs of priority
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texture measurements on vegetable tissue. You will participate in data collection and analysis and collaboratively advance the development of standard operating procedures for advanced microscopy. Learning
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-quality issues in bulk storage and food facilities. You will join and learn from a community of scientists and post-docs in the unit engaged in efforts to integrate and analyze data from volatile-gas
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development, and evaluation, by learning to implement automation, integrating data across systems (SharePoint, Teams, Salesforce, and 1CDP (Palantir System), and creating operational dashboards under