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affect oyster phenotypes targeted for improvement. The fellow will also gain experience using advanced computational methods to develop tools that can accurately predict desirable phenotypes. With
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Program of the USDA ARS offers research opportunities to motivated postdoctoral fellows interested in solving agriculture-related problems at a range of spatial and temporal scales, from the genome
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Project: The participant will have the opportunity to take part in the Methods and Applications of Food Composition Laboratory effort to improve the speed, accuracy, and/or sensitivity of methods
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-performance computing (HPC) systems for large-scale data processing, parallelized workflows, and computationally intensive analyses. Demonstrated experience applying phylogenetic and phylodynamic methods
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. Scientists in this unit maintain a comprehensive IAV research program including investigation of virulence mechanisms, vaccinology, immunology, and virus evolution. The participant will be based
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will 1) learn methods to conduct whole genome expression analyses (RNA-seq) of plant/pathogen and plant/insect interactions, 2) learn bioinformatic methods to identify and characterize candidate genes
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techniques to investigate off-flavor compounds in water and food systems. With mentor guidance, they will develop optimized sample preparation workflows and instrumental quantification methods to enhance
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the production, value, and safety of pecan, peach, nectarine, and plum crops. The participant will learn how to develop methods to improve control of key pecan diseases. The primary disease focus is pecan scab
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, outreach, and program evaluation to advance the South Central CASC's mission. Under the guidance of a mentor, specific activities include, but are not limited to: Communications Research and Synthesis
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Raman imaging technologies for safety and quality evaluation of agricultural products. Learn artificial intelligence/machine learning methods to evaluate hyperspectral image data to assess safety and