The PhD program in Computational Science produces mathematical scientists who bring the latest in computational methodology and problem solving to a variety of academic and industry settings.

Offered in collaboration with San Diego State University’s Computational Science Research Center, CGU’s PhD in Computational Science emphasizes interdisciplinary scholarship over specialization. Students learn to export computational and mathematical methods and applications across disciplinary boundaries while conducting graduate-level research. You’ll undertake collaborative research with faculty at CGU and SDSU who possess extensive backgrounds in applied mathematics, computational science, statistics, physical sciences, industrial modeling, and more. Our program creates versatile computational researchers who are prepared to contribute to research and development in modern academic, government, and industrial settings.

Program Highlights

Program at a Glance

72 units

3–5 years

Cost Per Unit 2017–2018: $1,902

Claremont, CA | San Diego, CA


SDSU Computational Science Research Center

PhD in Computational Science

Featured Courses

MATH 352
Nonparametric & Computational Statistics

Analyzes the treatment of statistical questions that do not depend on specific parametric models.

MATH 368
Numerical Methods for Matrix Computations

Examines numerical linear algebra and the matrix computations that arise in solving linear systems, least-squares problems, and eigenvalue problems for both dense and sparse matrices.

MATH 239
Fourier Analysis

Examines the difficulties involved in reconstructing arbitrary functions as infinite combinations of elementary trigonometric functions.

MATH 355
Linear Statistical Models

Discusses linear statistical models in full and less-than-full rank cases, the Gauss-Markov theorem, and applications to regression analysis, analysis of variance, and analysis of covariance.

MATH 353
Asymptotic Methods in Statistics With Applications

Examines modes of convergence for random variables and their distributions, central limit theorems, laws of large numbers, statistical large sample theory of functions of sample moments, and more.

MATH 387
Discrete Mathematical Modeling

Explores techniques in discrete mathematical modeling, including combinatorial analysis, Markov chains, graph theory, optimization, algorithmic behavior, and more.

View All Mathematics Courses


Field Experience
You’ll find opportunities to gain field experience through clinics and internships in a range of industry, business, and government settings, including NASA’s Jet Propulsion Laboratory and Boeing Company.

IMS partnerships expand your academic opportunities and include:

Claremont Center for the Mathematical Sciences
Through CCMS, you’ll have access to one of the largest mathematical science communities in California as well as workshops, conferences, and seminars, including:

  • Southern California Analysis Seminar
  • Math-in-Industry Workshop
  • Michael E. Moody Lecture Series
  • History and Philosophy of Mathematics Seminar
  • Claremont Mathematics Weekend
  • CCMS Software Lab and more

Learn More

Faculty & Research

  • John Angus profile image

    John Angus

    Professor of Mathematics
    Director, Institute of Mathematical Sciences

    Research Interests

    Probability, Statistics, Computing, Algorithms, Navigation, Systems Engineering, Mathematical Finance

  • Marina Chugunova profile image

    Marina Chugunova

    Associate Professor of Mathematics
    Program Director, PhD in Engineering & Industrial Applied Mathematics

    Research Interests

    Surfactant-driven thin film flows in biomedical applications; Nonlinear parabolic equations; Stability problems in fluid dynamics; Scientific computations; Applied operator theory; Sturm-Liouville problems

  • Ali Nadim profile image

    Ali Nadim

    Professor of Mathematics
    Joseph H. Pengilly Chair in Mathematics

    Research Interests

    Fluid Dynamics, Mathematical Modeling, Scientific Computing

  • Qidi Peng profile image

    Qidi Peng

    Research Assistant Professor of Mathematics

    Research Interests

    Statistical inferences, Stochastic differential equations, Stochastic modeling, Simulation, Machine learning, Approximation theory, Graph theory

  • Allon Percus profile image

    Allon Percus

    Professor of Mathematics

    Research Interests

    Discrete optimization; Network models; Statistical physics; Random combinatorial structures

  • Hrushikesh Mhaskar profile image

    Hrushikesh Mhaskar

    Research Professor of Mathematics

    Research Interests

    Approximation theory, Computational harmonic analysis, Mathematics of data, Query processing

  • Henry Schellhorn profile image

    Henry Schellhorn

    Associate Professor of Mathematics
    Academic Director, Financial Engineering Program

    Research Interests

    Financial engineering, Credit risk, Interest rate models

  • Claudia Rangel profile image

    Claudia Rangel

    Adjunct Professor of Mathematics

    Research Interests

    Probabilistic methods in computational biology, Statistical inference of genetic networks, Bioinformatics

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Jake Campbell

Senior Assistant Director of Admissions and Veteran Outreach
T: 909-607-7811