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the shallow subsurface (<10 meters depth). Experience with soil moisture/salinity and sapflow sensors. Experience using neural networks and machine learning tools. Stipend $70,000.00 – $80,000.00 Yearly Point
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are highly desirable. Familiarity with data science and machine learning applications for analytical chemistry, industrial/agricultural facilities, and techno-economic or life-cycle analysis is considered a
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also receive training in use of Excel spreadsheets, PowerPoint, Visio, and plotting and statistical analysis using various software platforms. Learning Objectives: Under the guidance of a mentor you will
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. Learning Objectives: By the end of this training/research experience, you will be able to: Explain the structure and functional organization of plant, insect, and/or fungal genomes and describe how genomic
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in a Unix environment and on high-performance computing equipment. Learning Objectives: Under the guidance of a mentor, you will have the opportunity to learn to: (a) apply methods in computational
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genetic tools; analyzing and summarizing research data for internal and external reporting; and assisting in the preparation of manuscripts for submission to peer-reviewed journals. Learning Objectives
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well as communicate with research networks within the scientific community. Learning Objectives: As part of this learning experience, you may: Learn how grapevine populations and germplasm are evaluated to identify
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validating the gene functions with transformation and molecular experiments. Lastly, you will assist in analyzing the gene-edited plants to improve grain quality in barley and oat. Learning Objectives: You
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primary learning experiences. You will examine the susceptibility of table grape breeding lines to gray mold caused by Botrytis cinerea, including developing and conducting scalable, high-throughput
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Programs 305 (Crop Production) and 304 (Crop Protection & Quarantine). Throughout the course of this project, you will learn about project management by contributing to research evaluating herbicide efficacy