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. Learning Objectives: The participant will learn skills in the Protein Function and Phenotype Prediction SCINet group. They will learn to develop and deploy AI-based protein structure prediction tools
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fruit, nut, and beverage germplasm collections to inform advanced breeding strategies and improve germplasm management. Learning Objectives: The participant will partner with the mentor to learn more
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resistance breeding efforts, ultimately benefiting soybean growers across the Midwest. Learning Objectives: Under the guidance of a mentor, the participant will learn: To prepare next-generation sequencing
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statistical software. Learning Objectives: Learn about the implementation of the application of machine learning methodologies in plant phenotyping and genotyping for the sugarcane molecular biology lab. Learn
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extended crop rotations. Learning Objectives: The intended outcome of this research is to improve nutrient-use efficiency in conventional Midwestern corn-soybean production systems, to increase the use
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diseases in cereal crops. Learning Objectives: This project will offer training and experience in a variety of molecular biology techniques used in studying plant-pathogen interactions. The candidate will
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mass spectrometry instruments, perform sample preparation, instrumental and data analysis, and write scientific per-reviewed manuscripts and reports. Learning Objectives: The participant will learn
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field production stakeholder, which requires an elevated level of coordination and communication. Learning Objectives: Learn internal and external sample collection and storage. To collect, analyze and
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, antibody assays, etc.), and report research results in scientific journals. Learning Objectives: The participant will collaborate with a diverse team of virologists, immunologists, bioinformaticians, and
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based on participant’s skills and interest. Learning Objectives: Under the guidance of a mentor, the participant will help conduct research to study the immune responses to viral challenge in pigs with