107 parallel-processing-bioinformatics Fellowship positions at Zintellect in United States
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in applying process-based cropping system models to quantify the short- and long-term effects of these conservation practices on soil health and crop productivity for U.S. growers. This specific
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sensing and decision-making in poultry processing environments. Learning Objectives: Under the guidance of a mentor, the participant will gain knowledge and experience in: Applying hyperspectral imaging
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improvements in different production traits. In parallel, a single cell atlas for turkey immune organs will be developed for use in downstream gene editing applications. Learning Objectives: The fellow will
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bioinformatics analysis. Learning Objectives: You will receive training in handling various viruses and gain experience in different sample processing procedures to extract nucleic acids for NGS and learning
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(e.g., enhancers, promoters) in cattle. Customize bioinformatics pipelines for automated processing and analysis of short- and long-read sequencing data. Apply computational approaches to detect genetic
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insurance can be obtained through ORISE. Questions: Please visit our Program Website . After reading, if you have additional questions about the application process, please email ORISE.ARS.Northeast@orau.org
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portfolio including plant science, soil health, bioinformatics, protecting agricultural against invasive species, natural resources, remote sensing, advanced manufacturing, and the nexus of agriculture and
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Objectives: Through this fellowship, you will gain valuable hands-on experience and develop expertise in laboratory research and bioinformatics. You will have the opportunity to learn and enhance skills in
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available, including hardware focused on AI approaches which can be utilized by this project, including training and professional development opportunities in bioinformatics and data science and a large
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skills in novel bioinformatics-based tools for analyzing and interpreting genomic, metagenomic, and/or gene expression datasets from animals and microbes, particularly in response to emerging Salmonella