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. The participants will collaborate on this project under the mentor's guidance. They will participate in research and analysis of results and evaluate their relevance to food quality and safety. Learning Objectives
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, physiology, and or genetics of invasive wood-boring insects and their natural enemies Data management and statistical analysis for laboratory and field experiments on insect behavior Being a part of projects
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productive under sustainable management systems. Learning Objectives: The participant will gain skills in laboratory methodologies, experimental design, maize breeding, and data analysis. Through the course
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analysis of large, diverse datasets including field experimental data, geospatial data, and time series data. Experience with machine learning and statistical learning. Familiarity with various management
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analytical software for data analysis to include ArcGIS, Kaleidoscope Pro, and R. Other activities will include entering data, transferring acoustic files, data management, keeping accurate notes, and
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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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and tools for transformation analysis. Conducting phenotype trials related to sugarcane genetics and genomics. Helping scientists with trials for CP sugarcane breeding and flower synchronization
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high-containment (BSL-2) environments, including conducting vaccine safety and efficacy trials. Bioinformatics: Familiarity with computational tools for NGS sequence analysis, transcriptomics (RNA-seq
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and ion), mass spectrometry, and capillary electrophoresis. Learning Objectives: Become familiar with the collection, extraction and analysis of horticultural samples Develop skills in the following
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an early-stage project from initiation to analysis to a fielded system in a short period of time. The knowledge gained will provide you a highly desired skill set in the area of clinical systems