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models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science
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phylogenetic trees and genotype populations. · Be able to do statistical analysis. · Basic knowledge of mycology and taxonomy of fungi and oomycetes. · Understand the basic principles of microscopy and be able
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 15-Jul-25 Location: Syracuse, New York Type: Full-time Categories: Academic/Faculty Mathematics/Statistics Internal
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project funds are secured and from a non-federal source. The position involves applying bioinformatic and statistical tools to existing multidimensional datasets, including metagenomic, transcriptomic
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
. Eligibility is currently open to: U.S. Citizens; U.S. Lawful Permanent Residents (LPR); Foreign Nationals eligible for an Exchange Visitor J-1 visa status; and, Applicants for LPR, asylees, or refugees in
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findings. Knowledge, Skills, and Abilities: Knowledge of coordinating experiments, and completing analysis, statistics, and interpretation. Ability to communicate in a clear, concise manner orally and in
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experience. For questions regarding the position, please contact Dr. Sushan Ru at sushan.ru@auburn.edu The Program: The Small Fruit Breeding Program at Auburn University is located in Auburn, Alabama, U.S
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, perform statistics on soil test correlation and calibration datasets, and develop presentations and manuscripts for publication. This postdoctoral research scholar will work closely with the programmer to
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Requisition Id 15076 Overview: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges
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advanced statistics. · Practice Experience: RN experience in a U.S. healthcare system. · Methodological Skills: Proficiency in both qualitative and quantitative research methods. Experience with data