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: Enrollment in a Master's or PhD program for Mathematics or related field Familiarity with math software/tools (e.g., MATLAB, graphing calculators, Microsoft Excel, R) Additional Information: This is a part
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o Theoretical and Computational Biophysics o Soft Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal Graph Theory, Computing Theory o Programming
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has a strong PhD program in Applied Mathematics, Applied Statistics, Graph Theory/Combinatorics, and Analysis, featuring active research collaborations both within the University and with external
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University of Texas at Arlington, Department of Mathematics Position ID: UTArlington -AICLUSTER [#26180] Position Title: Position Type: Tenured/Tenure-track faculty Position Location: Arlington
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Learning (especially deep and reinforcement learning) Numerical Analysis or High-Performance Computing Symbolic Computation Solvers Dynamical Systems / Control Theory Discrete Mathematics, especially Graph
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probability, random matrix theory, random graphs, stochastic analysis, and stochastic processes. Preference will be given to applicants with demonstrated research interests or expertise in the development
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(OTUs) in microbial communities using graph theory and the Slope-Matrix-Graph (SMG) algorithm. The student will be actively involved in algorithm design, data analysis, and result presentation, gaining
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Grossmont/Cuyamaca Community College District | El Cajon, California | United States | about 1 month ago
mathematics, formal logic, graph theory, and their applications to computational problem-solving Computer architecture, operating systems, and the relationship between hardware and software systems Object
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research and publication. Additional Job Description Required Qualifications Ph.D. in Data Science, Analysis, Graph Theory, Algebra, Combinatorics, Applied Math or Statistics, or related area from a
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to implement and optimize AI/ML models for biomedical datasets. Preferred Knowledge, Skills and Abilities Mathematical Modeling: Strong foundation in numerical modeling, graph theory, and statistics. Algorithm