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background in addition to a good background in mathematical analysis. The project interacts with several areas of mathematics: computational harmonic analysis, approximation theory, orthogonal polynomials
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strongrecord of scientific productivity is preferable. The successful applicant must have a Ph.D.in Computer Science, Data Science, Statistics, Mathematics, Physics, Engineering orrelated field at the start of
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contributing to grant proposals. • Participate in teaching undergraduate courses (6 credit hours per year) Qualifications • Ph.D. in Operations Research, Industrial Engineering, Computer
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The successful applicant must have a Ph.D. in Computer Science, Data Science, Statistics, Mathematics, Physics, Engineering or related field at the start of the appointment. Type Benefited Staff Special
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involved in analyzing data collected from the TexNet seismological monitoring program and other stations or assets that provide quality data. Comparing different methods and tools for moment tensor inversion