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extractors. Hands-on training will be provided in the characterization of plant proteins, including assessment of secondary structure, surface charge and hydrophobicity, thermal properties, digestibility
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structures, molecular networks, and disease-resistance phenotypes. Artificial intelligence (AI), machine learning, and bioinformatics will connect genotypes with phenotypes and identify maize and fungal genes
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modification of low value waste materials and their derivatives. Physical, chemical and instrumental analysis of raw materials and finished products are used to determine the structural characteristic and
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to characterize the structure and function of plant, insect, and fungal genomes related to pecan cultivar development. Application of sequence resources from plants, pests, and pathogens will be directed towards
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of a mentor you will: Deepen expertise in cotton fiber chemistry and structure, gaining advanced training in analyzing moisture, wax, pectin content, crystallinity, and related functional traits under
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of synthesized compounds. Develop expertise in mass spectrometry as a tool for chemical identification and structural analysis. Understand applications of semiochemical chemistry in reducing pest pressure on
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. Regular mentoring interactions will provide structured opportunities to explore scientific concepts and professional development goals. Engagement with biologists and natural resource professionals across
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skills: Experience with synthetic organic chemistry, including chemical transformations, separations, purifications, and structural and chemical analysis, using MS and NMR. Experience and/or thorough
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relevant information from medical imagery, video feeds, and operational sensor streams. Building and integrating multi-modal models that fuse vision, text, audio, physiological signals, and structured