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: You will be trained in state-of-the-art methods for assessing iron bioavailability from foods and apply those methods to address stakeholder needs. You will also be trained in techniques of liquid
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agricultural yield prediction models for use in plant breeding through a combination of high-throughput phenotyping data, physiological crop growth modeling, and artificial intelligence methods. There will be
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, the participant will: (1) gain experience in computational modeling to optimize manufacturing high-purity reactive refractory metal powders, (2) learn advanced modeling methods based on density functional theory
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engage in a collaborative environment and learn from their mentor to develop their skills in entomological, molecular biology, and genomic research methods. This experience will further provide
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evaluation using mobile devices and high-throughput methods such as drones. Phenotypic evaluation will align agronomic traits with allele frequency using advanced statistics. The participant will have the
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barley and oat productivity, quality, and stress resistance by combing traditional, molecular, and genomics methods. The participant will be part of the research effort in the laboratory, greenhouse, and
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, developing, and, when necessary, modifying methods and procedures to best meet specific research goals. The participant will also learn to plan, implement, and maintain laboratory bioassays involving honey
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markers, and determination of bacterial and virus disease titers. Learning Objectives: Learn theory, methods, and skills to propagate citrus plants, prepare plants for greenhouse and field research, and to
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on developing answers to this question using quantitative and qualitative methods, for example, secondary data analysis and expert elicitation. Results are expected to help with USDA research
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computational and information sciences. About Photonics, Electronics, & Quantum Sciences (PE&QS) Materials (and related manufacturing methods) and devices intended for achieving photonic, electronic, and quantum