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methods to analyze large health databases, including electronic health records (EHR), and National Center for Health Statistics (BRFSS, NHANES, SEER). Required License/Registration/Certification N/A
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
information and library science with leadership in data science, including computational and statistical methods, and societal applications. Home to a top ranked library and information science program, SDIS is
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omics platforms (e.g., fluorescence microscopy, mass spectrometry imaging (MSI), Raman systems) and will develop computational and statistical data analysis methods to improve data quality, information
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state-of-the-art statistical and mathematical methodology to improve understanding of epidemic dynamics and control. They will work on one of the new projects starting in the Unit, including i) analysing
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Mississippi State University, Department of Mathematics and Statistics Position ID: MissState-STATISTICS1 [#27395] Position Title: Position Type: Postdoctoral Position Location: Mississippi State
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analysis of complex biomedical datasets. The research environment is highly interdisciplinary, bringing together expertise from machine learning, statistics, data science, and healthcare research
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of statistics is preferred. Experience with experimental work and molecular ecology methods is an asset. The candidate must demonstrate proven ability in independent scientific research and skills in writing
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methodology and public policy research on marginalized mountainous and highland areas Additional training in the field of spatial data analysis (GIS) and statistical data processing (SPSS Statistics or R
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lead advanced statistical analyses integrating ecological datasets with spatiotemporal modelling frameworks. The work will contribute with evidence-based data to development of ecosystem-based
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neurodegeneration and more specifically on Alzheimer’s, Parkinson’s and Huntington’s disease. The Postdoctoral Associate will work with Drosophila and cellular models of these disorders using genetic, statistical