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this information can improve our ability to predict the spread and intensity of wildfires and prescribed fires. Learning Objectives: The program participant will learn a variety of new skills to measure
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be focused on learning how to develop algorithms, performing biochar characterization tests, and characterizing microbial communities that colonize biochar in different ecosystems. Learning Objectives
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Transkingdom Microbial Community Assembly in the Barley Phyllosphere During Fusarium Infection.” Learning Objectives: Under the guidance of a mentor, the participant will learn how to: Perform statistical
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to improve soybean for enhanced disease tolerance by accelerating breeding programs and enabling the engineering of new and improved traits. Learning Objectives: As a result of this experience, the participant
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will focus on evaluating how alfalfa-grass interactions influence biological nitrogen fixation, soil health, and soil organic matter dynamics in mixed species forage production systems. Learning
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pursuing degrees in mathematics, computer science, computer engineering, or electrical engineering. These students possess strong mathematical and computer programming foundations and technical skills
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. This data was collected primarily in upland habitats, but a subset of the data focuses on changes in meadows over time. Learning Objectives: The selected fellow(s) in this project will have the opportunity
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. Investigate options to lower energy consumption and carbon intensity of downstream aspects of the production of packaged leafy greens. Learning Objectives: Under the guidance of a mentor(s), the selected
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techniques to enable regulatory agencies to evaluate better the risks associated with exposure to chemicals. Learning Objectives: The postdoctoral fellow will receive training in performing scholarly research
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using both conventional breeding methods and marker assisted breeding. Learning Objectives: The participant will partner with the mentor to learn more about: Conducting phenotype trials related to maize