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for a post-doctoral research associate in the area of mathematical and computational modeling of epidemiological risk in wildlife trade networks in the Fefferman Lab at the University of Tennessee
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, population ecology, spatial ecology, mathematical biology, or other similar fields. Demonstrated experience building and analyzing mathematical and statistical models aimed at answering biological, ecological
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) Doctoral Degree (or foreign equivalent) in Mathematics, Applied Mathematics, and Statistics, or closely related
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physical science and/or engineering research. Experience in simulation & modeling of fluid flow. Experience in statistical analysis and quality analysis. Demonstrated knowledge of advanced mathematics
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Qualifications PhD in Computational Science, Computer Science, Applied Mathematics, Engineering or Physics by the time the appointment begins. Additional Qualifications Applicants background may include studies in
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. Necessary skills include knowledge of post-processing software (e.g., Matlab, R, IDL) and/or statistical/mathematical programming languages (e.g., R, Matlab). Desirable skills include working knowledge
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Completed or soon-to-be completed PhD (within the last 0-5 years) in Computer Science, Physics, Mathematics, or related field Experience with modeling complex systems or natural language processing
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Qualifications • Doctoral degree in Aerospace Engineering, Electrical Engineering, Applied Mathematics, or related discipline. PhD must be awarded no more than four years prior to the effective date of appointment
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, deep learning, mathematical modeling, system identification, optimization, digital/mobile health, natural language processing, and data visualization. MINIMUM QUALIFICATIONS: A doctoral degree or
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 17 days ago
on biophysics and applied mathematics. Approaches in fields of network theory, machine learning, neural networks & deep learning, multivariate statistics, scientific visualization and nonlinear dynamics