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problems that also depend on collaboration across scientific disciplines and geographic locations. In addition, many of these technologies rely on the synthesis, integration, and analysis of large, diverse
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other test sites. Why should I apply? Under the guidance of a mentor, you will: Learn how to research issues and conduct feasibility studies pertaining to the engineering and scientific elements
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inference) Algorithmic development for bilevel (or multilevel) optimization Methodological developments in Bayesian statistics and/or decision analysis Application of adversarial risk analysis within security
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, scour-resistant features, and flood-risk-mitigation designs, building a broader appreciation for how computational methods support analysis of real-world hydraulic challenges. Along the way, you can
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tools are used to characterize genetic and epigenetic variation. Identify and differentiate types of genomic variation (e.g., SNPs, CNVs, DNA methylation patterns) and functional genomic elements (e.g
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genomics and II. Barley and oat molecular biology. For the first project, you will help conduct genetic analysis of resistance to stripe rust and hessian fly in barley and map the key genes or QTLs related
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demonstrations aimed at integration into ongoing or upcoming NASA missions and proposal opportunities. The specific research topics include RF component-level development, light-weight, high-gain antenna systems
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analysis, and data dissemination. Searching, synthesizing, and interpreting information relevant to public health. Conducting literature reviews to identify evidence-based methodologies for measuring and
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texture measurements on vegetable tissue. You will participate in data collection and analysis and collaboratively advance the development of standard operating procedures for advanced microscopy. Learning
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transcriptomic and other genomic analysis approaches Apply laboratory techniques, sample processing, and data interpretation in a research setting Mentor(s): The mentor for this opportunity is David Holthausen