66 parallel-computing-numerical-methods Fellowship positions at Zintellect in United States
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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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-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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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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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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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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, 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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using both conventional breeding methods and marker assisted breeding. Learning Objectives: The participant will partner with the mentor to learn more about: Conducting phenotype trials related to maize
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conventional breeding methods and marker assisted breeding. The overall objective of the research is to develop and release germplasm, methodology and information that will expedite the development and
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quality attributes and resistance to diseases and pests, as well as a tolerance to environmental stresses. This will be achieved through a combination of traditional breeding methods, molecular techniques
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, the fellow will have the opportunity to collaborate on related research including eDNA detection methods and mapping populations across the growing region. Learning Objectives: Under the guidance of a mentor