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to quantify pathogen load in samples and metagenomics and bioinformatics to understand genetic diversity of the pathogen. Potential areas of research include genomic epidemiology, ecological surveillance, and
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problems. Methodologies used by the fellow range from those requiring considerable modification to routine, and include plant genetics, molecular biology techniques, computational biology/bioinformatics
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, bioinformatics, precision technologies, agronomy, and reproductive physiology in beef cattle, as well as opportunities for collaboration and networking. Mentor(s): The mentor for this opportunity is Brittany Davis
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, diagnostic assay development, high-throughput sequencing, multi-omics research, and/or bioinformatics. Experience using advanced scientific technologies to creatively solve agricultural challenges is
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assessment of mutations) Demonstrated skill and practical experience in molecular biology techniques (e.g., nucleic acid purification, gene amplification and cloning, bioinformatic analysis of genomic data
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breeding and molecular biology. Learning Objectives: As a result of this experience, the participant will: Learn methods to conduct transformation of sugarcane, Learn genomics, bioinformatic methods
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signaling. Learning Objectives: The participant will gain skills in bioinformatics, genetics, data analysis, statistics, and artificial intelligence-based methods for protein modelling. The participant will
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blotting or ELISA for protein detection is highly desirable. Additionally, the ideal participant will demonstrate an interest in using bioinformatic tools for data interpretation and a commitment to
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Learning about protein design and engineering Exploring cell-based and cell-free screening Applying high-throughput screening Utilizing bioinformatics, machine learning, and other computational approaches
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pathogens, microbial community characterization, plant tissue culture, diagnostic assay development, high-throughput sequencing, multi-omics research, and/or bioinformatics. Experience using advanced