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-based experiments, culture assays and molecular work, multi-omics techniques, and establishing bioinformatic pipelines for data analysis. The ideal candidate will demonstrate the ability to integrate
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 2 months ago
of Applied Social Sciences (DASS) seeks applications for two (2) Post-Doctoral Fellows within the Rural and Farm Finance Policy Analysis Center (RaFF) at the University of Missouri. RaFF provides U.S. Congress
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utilizing animal models and the downstream isolation and analysis of immune cells using a variety of techniques including, but not limited to, flow cytometry, ELISA, RT-PCR, bulk and single cell RNA
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). This would be expected to include independently performing experiments utilizing animal models and the downstream isolation and analysis of immune cells using a variety of techniques including, but not limited
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analyses, including, but not limited to, structural equation modeling, multilevel modeling, longitudinal analysis, and other advanced statistical approaches relevant to population health and health
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research associate to advance the analysis, quality assurance, and calibration of automated pavement condition data and pavement performance modeling. The successful candidate will contribute to two
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standard molecular simulation/analysis tools (e.g., AMBER, VMD, PyMOL, Chimera, Cpptraj). ● A track record of first-author publications in peer-reviewed journals, and strong written and oral
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theory, analysis of Roman commissioning and early GBTDS data, support for event-analysis and planet occurrence-rate pipelines, and the publication of scientific results based on Roman exoplanet data
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engineering and protein biochemistry is essential. Experience in -omics methods, as well as in protein production and characterisation (FPLC, WB, etc.), is required. Skills in the analysis of omics data and the
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an understanding of the ecological and evolutionary basis of adaptation and stress responses; demonstrated expertise in genomic data analysis and strong quantitative/bioinformatic skills, including relevant