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Department Information

Our department fosters a supportive environment through hands-on instruction while promoting the proficiency needed to prepare students for a wide range of career possibilities. Particular strengths as a department include computational and applied mathematics. The department offers M.S. and Ph.D. degrees in computational and applied mathematics.

Current research includes numerical analysis and scientific computation, dynamical systems, fluid dynamics, electromagnetics, data science, mathematical biology and computational neuroscience.

Program Features

The Department of Mathematics offers one of the country's leading programs for those who want to pursue graduate studies in computational and applied mathematics. The program specifically emphasizes physical applied mathematics, numerical analysis, and scientific computation.

Students selected for this program will study under a distinguished faculty that consists primarily of numerical analysts and applied mathematicians. In keeping with a long-standing SMU tradition, all faculty members, including our endowed chair holder and other senior professors, are required to teach graduates and undergraduates. With a 1-1 ratio of graduate students to faculty members, graduate students can be assured of individual attention.

SMU also offers excellent computer facilities, an outstanding library collection, competitive financial aid, and the advantage of being located in an area where job prospects for graduates are plentiful.

Degrees Offered

Explore our Computational and Applied Mathematics M.S. Program

Explore our Computational and Applied Mathematics Ph.D. Program

Computational and Applied Mathematics Program Features at SMU

The Computational and Applied Mathematics program has the goal of maximizing your knowledge in a chosen specialization and preparing you for research and a future career in academia and/or private industry.

Center for Scientific Computation

Center for Scientific Computation

 

The mission of the Center for Scientific Computation (CSC) at Southern Methodist University is to stimulate interdisciplinary education and research in simulation-based engineering and science.

 

ManeFrame II (M2): SMU’s new high-performance compute cluster will dramatically increase the computational capacity and performance that SMU provides to its researchers. The new cluster features state of the art CPUs, accelerators, and networking technologies, significantly more memory per node, and advanced interactive GPU-accelerated remote desktop experiences. Also, the cluster is much more energy efficient making it more economical to run and more environmentally friendly.

Dedman College Interdisciplinary Institute

Dedman College Interdisciplinary Institute


The Dedman College Interdisciplinary Institute (DCII) encompasses all the divisions within Dedman College: humanities, social sciences, and sciences which includes mathematics and statistics. It also reaches out through its programs to the rest of the University and to the local community, creating a culture of interdisciplinary inquiry and bridging the physical sciences and the humanities, the liberal arts and the professional schools, and academia and the broader community.

Admission Requirements

  • 18 credit hours of college-level mathematics (courses beyond first and second-year calculus)

  • Official Transcripts

  • GRE Score

  • Recommendation Letters

  • Statement of Purpose

Students in the Ph.D. program will be awarded the M.S. degree en route to the Ph.D.

  • 18 credit hours of college-level mathematics (courses beyond first and second-year calculus)

  • Official Transcripts

  • GRE Score

  • Recommendation Letters

  • Statement of Purpose

Students in the Ph.D. program will be awarded the M.S. degree en route to the Ph.D.

Deadlines for Admission

For graduate Computational and Applied Mathematics programs:

  • Priority deadline for Fall admission to the Ph.D. program is January 15th.
  • Final deadline for Fall admission to the M.S. program is May 1st


Departmental Assistantships

For students in the Ph.D. program there is financial support in the form of teaching and research assistantships that includes full tuition and a competitive stipend.  For exceptionally qualified applicants the university offers a limited number of Ph.D. Fellowships.

Applications for financial support must be received by the priority deadline.

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Degree Requirements

  • 33 total credit hours
  • 2 required computational mathematics courses
  • 2 required “differential equations and their applications” courses

  • 7 approved elective courses

  • Oral examination
  • All requirements for Computational and Applied Mathematics M.S. (plus additional coursework)
  • 18 total credit hours

  • 6 hours of dissertation credit

  • Completion of the qualifying examination

  • Successful defense of the PhD dissertation

Alumni Spotlight

jean-sexton

Jean Sexton, Ph.D. 2017

Jean received her Ph.D. in Computational and Applied Mathematics from Southern Methodist University in 2017. Her dissertation research fits broadly in the applied mathematics fields of scientific computing and numerical analysis. Specifically, she focused on the development of numerical methods for the time integration of problems with multiple characteristic time scales.

These methods are motivated by multiphysics, multiscale real-world application problems which are constructed by coupling physical processes with potential disparate length and time scales. Jean developed a family of efficient, fully coupled fourth-order multirate method with comparable stability properties to leading existing third-order multirate methods. These methods were based on existing Recursive Flux-Splitting Multirate methods using Generalized Additive Runge-Kutta theory to analyze order conditions.

Jean is currently working as a postdoctoral researcher in the Center for Computational Sciences and Engineering (CCSE) in the Computational Research Division of the Computing Sciences Directorate at the Lawrence Berkeley National Laboratory. She is interested in improving efficiency for simulations involving time integration methods.

This story originally appeared on the CCSE Berkeley website.

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