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relevant programming languages. Ability to use/learn several advanced modeling methods (e.g., statistical, mathematical, individual-based, or machine learning models). Experience with high-performance
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relevant programming languages. Ability to use/learn several advanced modeling methods (e.g., statistical, mathematical, individual-based, or machine learning models). Experience with high-performance
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Florida State University, Mathematics Position ID: FSU-PDMATH [#25544] Position Title: Position Type: Postdoctoral Position Location: Tallahassee, Florida 32306, United States of America [map
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Ph.D. by the time of appointment in statistics, mathematics, computer science, engineering or a related discipline Required Other None Additional Preferred Experience working in one of the following
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
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, Nanomedicine & Advanced Therapeutics at the Department of Pharmacology and Pharmacy (several posts) (Ref.: 532606) We now invite applicants to join the Science, technology, engineering, and mathematics Lab
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welcomes applications for postdoctoral positions in the mathematical sciences. These are two year positions, and may be extended by another year. The Center is seeking in particular candidates with a strong
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to disseminate research results QUALIFICATIONS Applicants must have (or be about to receive) a PhD in physics, biophysics, systems biology, applied mathematics, bioengineering, chemistry, chemical engineering, or
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epidemiological modeling. Prior experience with mathematical modeling of vector-borne disease and gene drive control systems. Knowledge, Skills, and Abilities Programming skills in R or Python. Ability to work
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Postdoctoral Associate — Bioinformatics and Data Science - Stites Laboratory The Stites laboratory utilizes a variety of computational, mathematical, and experimental methods to study problems in