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, and analysis of DPS partner investment data. Collaborate on the development and expansion of a dashboard to collect, store, visualize, and analyze DPS science and evaluation science data. Learning
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interacts with the human body—making it a key factor in both product performance and consumer satisfaction. You will also apply statistical and machine-learning tools to explore how cotton fiber properties
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USDA-ARS High-Throughput In Vitro Screening of Antimicrobial Compounds Against Phytoplasma in Cherry
. For more information on the agency, visit the USDA Agricultural Research Service Home Page . Research Project: You will engage in a collaborative research initiative focused on evaluating therapeutic
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. You will have the opportunity to collaborate with the lab team and the epidemiology team to learn how to enhance communication and may collaborate with electronic report management system. You will have
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analyses. Learning Objectives: By collaborating closely with members of our interdisciplinary research team, you will gain invaluable hands-on experience to all phases of the research process. You will
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where new health hazards (such as vapor intrusion or changes in chemical toxicity) have emerged. Learning Objectives: You will have the opportunity to: Learn ATSDR’s approach to conducting public health
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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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development, and evaluation, by learning to implement automation, integrating data across systems (SharePoint, Teams, Salesforce, and 1CDP (Palantir System), and creating operational dashboards under
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to CDC's efforts to better understand the burden of CKD and inform public health strategies to improve prevention and outcomes. Learning Objectives: You will have the opportunity to advance your skills
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primary learning experiences. You will examine the susceptibility of table grape breeding lines to gray mold caused by Botrytis cinerea, including developing and conducting scalable, high-throughput