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sequencing in cattle. Developing better statistical methods to improve association studies with QTL and enhancing genetic prediction tools for automation of data processing required for SNP use in livestock
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techniques, modern sequencing technologies, advanced statistical and computational tools, and interdisciplinary teamwork. Mentor(s): The mentor for this opportunity is Yulin Jia (yulin.jia@usda.gov ). If you
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of the relevant fields. Preferred skills: Previous experience in computational ecology and statistics. R or Python. Statistical analysis tools such as NIMBLE, JAGS or STAN. Familiarity with data processing, quality
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genomics, RNA-seq, genome assembly, variant calling, and other high-throughput sequencing approaches. Advanced proficiency in bioinformatics tools, pipelines, and statistical methods for the analysis
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Statistics (11 ) Physics (16 ) Science & Engineering-related (2 ) Social and Behavioral Sciences (29 ) ORISE GO The ORISE GO mobile app helps you stay engaged, connected and informed during your ORISE
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Sciences (17 ) Earth and Geosciences (21 ) Engineering (29 ) Environmental and Marine Sciences (14 ) Life Health and Medical Sciences (51 ) Mathematics and Statistics (11 ) Physics (16
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Geosciences (21 ) Engineering (29 ) Environmental and Marine Sciences (14 ) Life Health and Medical Sciences (51 ) Mathematics and Statistics (11 ) Physics (16 ) Science & Engineering-related (2
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. Conducting descriptive and inferential statistical analyses. Contributing to publications in peer-reviewed scientific journals. Where will I be located? This opportunity is 100% remote. What is the anticipated
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, including data preprocessing, feature engineering, and preparation of datasets for robust model training and validation. Experience with computational and statistical analysis in Python and R. Familiarity
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be familiar with at least one statistical package or R. Excellent writing and presentation skills for proposal development, scholarly papers, and scientific presentations. Training in entomology with