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approaches are used to address real-world challenges in the food industry. The participant will collaborate with chemists, material scientists, plant scientists, and food engineers to build a comprehensive
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opportunities designed to build expertise at the intersection of data science, artificial intelligence, and regulatory science. These include: Mentored research experiences with FDA subject matter experts in data
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, including barley bacterial leaf streak, Fusarium head blight, and oat stem and crown rust. Build skills in gene mapping and molecular-marker development for disease-resistance traits. Gain experience with
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help you build skills in data analysis, written and oral communication, organization, collaboration, and public health emergency response. You will also gain experience in a fast-paced public health
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to make models realistic, and analyzing output from simulation runs using established statistical techniques. Opportunity exists for novel approaches, and you will be encouraged and supported to publish
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analytical technique. Build an understanding of pharmaceutical dissolution and drug-release principles and learn to evaluate relationships between formulation microstructure, chemical distribution, material
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breeding, genomics, quantitative genetics, biotechnology, horticulture, and pre-breeding approaches used to improve stress tolerance in grapevine breeding lines. Learn how researchers make crosses, evaluate
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to make all division products and activities scientifically strong, clear, compelling, and leading to action. The DPS SEU promotes excellence in science and evaluation through data quality, scientific
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, including models customized for fungal genomes. Training will include crop and fungal RNA-seq analysis; integration of multi-omic and phenotypic data; protein-interaction and structure-based analyses; and
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and reproducible data, along with the ability to collect, process, and analyze such data effectively. Build proficiency in microscopy techniques and microbial enzyme assays, enhancing understanding