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USDA-ARS Molecular Biology Postdoctoral Fellowship in the Natural Products Utilization Research Unit
involving physiological, biochemical, and molecular experiments and the use of numerous techniques such as RNA-seq, data mining of DNA and protein sequence databases, analysis of gene function via CRISPR/Cas
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—from chickens to bison and everything in between. This opportunity is in the endemic swine viruses laboratory group of the Virus and Prion Research Unit, which advances a comprehensive research program
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genetic, genomic, and phenotypic datasets, to support research and crop improvement. Basic and applied research is also conducted within this project. You will use methods in computational biology to
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for Grain and Animal Health Research in Manhattan, KS. Our mission is to develop economical, effective, and ecologically sound methods for managing insect pests of grain and processed commodities, improve
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phenotyping methods to assess susceptibility and evaluate established or newly developed screening approaches. This also includes developing and evaluating preharvest and postharvest treatments aimed
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—from chickens to bison and everything in between. This opportunity is in the endemic swine viruses laboratory group of the Virus and Prion Research Unit, which advances a comprehensive research program
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contingent on the availability of funds. Level of Participation: The appointment is full time. Participant Stipend: Stipend rates may vary based on numerous factors, including opportunity, location, education
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language processing, data science, computational methods, or related quantitative approaches. Experience with Python, R, SQL, or other analytical or programming tools. Strong analytical and critical-thinking skills and
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industrial desert crop to farmers in the south western US as an alternative to high water requiring crops such as as cotton and alfalfa. Current methods will be optimized and new methods may be invented and
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managing diabetes using computer simulation models. Learning Objectives: You will learn: How to synthesize and translate empirical evidence on cost-effectiveness of interventions for the prevention and