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statistical and clinical reviewers to research and develop a practical framework for selecting (primary) endpoint strategies and determining the corresponding statistical analysis plan for non-malignant
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avian influenza (HPAI) airborne transmission between U.S. poultry facilities. The primary focus of this opportunity will be learning to develop statistical and mathematical models to assess airborne
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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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skills: Experience in statistical programming in languages such as R (ideal) or Python. An understanding of linear models and probability. A background in biology, with a preference for cellular biology
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, including measuring in planta defense phytohormones; and, 6) modern statistical analysis techniques via research collaborations with Iowa State University’s Statistics Department. Learning Objectives
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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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Requirements Citizenship: U.S. Citizen Only Degree: Doctoral Degree. Discipline(s): Computer, Information, and Data Sciences (2 ) Life Health and Medical Sciences (8 ) Mathematics and Statistics (3 ) ORISE
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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