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areas. These include, but are not limited to: Applying machine learning algorithms to solve real-world problems. Creating and structuring databases for storage, retrieval, and image analysis. Determining
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learning about the scientific process and field sampling methods. The fellow will also learn to identify common plant species of the interior Pacific Northwest, collect and process increment cores for tree
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, cell-based assays, and quantitative immunologic methods to measure functional antibody activity. Learning Objectives: Under the guidance of a mentor, you will have the opportunity to: Learn
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mycobateria and brucella families in various species of animals using serological tests as part of the eradication program. Learning Objectives: The participant will have the opportunity to learn about zoonotic
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Project: This research is a component of ARS National Programs 305 (Crop Production) and 304 (Crop Protection & Quarantine). Throughout the course of this project, the participant will learn about project
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Salmonella detection methodologies. Learning Objectives: The participant will learn about stakeholder-focused research, data science, scientific communication, food safety applications, real-world data, and
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integrating advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques with process-based crop models, this research will empower farmers to optimize conservation practices, increase
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strategies to improve safety and efficacy of T cell therapies. Learning Objectives: The overall learning experiences you will gain are as follows: Will learn to perform laboratory research on projects related
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research under strict biocontainment parameters. Learning Objectives: During the appointment, you will; Develop knowledge of integrative genomic and biological approaches used to detect and manage emerging
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, economic evaluation, and surveillance to learn how to operationalize, and when needed, improve analytical tools. Research activities will support rapid risk assessment, emergency preparedness, and