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Field
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, computer science, artificial intelligence, or a related quantitative field Experience with mathematical/statistical modeling and/or machine learning/Al methods Strong interest in infectious disease epidemiology
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, Fisheries Science, Biology, Zoology, Biological Oceanography, Mathematics, Statistics, Computer Science, or related discipline Knowledge of modeling ecosystem and/or social network dynamics Strong
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disease with a focus on Alzheimer’s Disease. Computational models will be developed that utilize data obtained from a wide range of experiments, from basic biochemical methods to advanced imaging techniques
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in R, Mplus, AMOS or other latent variable modeling software program Programming: R Population health or health systems Doctoral degree: A doctoral in social sciences (e.g. sociology, psychology
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-month, non-tenure track, appointment. Required Qualifications Earned PhD, ScD or DrPH in public health, epidemiology, biostatistics, statistics, mathematics, data sciences, or computer sciences, or a
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cytoskeleton and membrane trafficking. • Utilize quantitative, biophysical, and computational approaches to cell biology, including fluorescence imaging, image analysis, and biophysical modeling. • Experiment
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Job Description Required Qualifications: (as evidenced by an attached resume) Ph.D. (or foreign equivalent) in Electrical Engineering, Computer Science, Applied Mathematics, or a closely related field
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Job Description The Opportunity The Department of Aerospace Engineering, at the Daytona Beach Campus seeks a post-doctoral researcher to develop novel mathematical and computational tools
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 16 hours ago
research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our research enterprise and
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workplace – in how we treat one another, work together, and measure success. Basic Qualifications: Ph.D. in computational data sciences and engineering, applied mathematics, geography, statistics, computer