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The MS in Computational & Applied Mathematics trains you in the analytical and numerical methods of applied mathematics to address and solve pressing challenges in all areas of science and engineering.

Mathematical modeling and scientific computing have become increasingly useful problem-solving tools. You’ll learn analytical and numerical methods of applied mathematics, applying them to problems in physics, biology, engineering, economics, climate science, and more. You’ll work alongside faculty who have extensive backgrounds in applied mathematics, computational science, statistics, financial engineering, industrial modeling, and related fields. Our program produces educated, capable practitioners who excel at communicating knowledge and solving complex mathematical challenges across disciplines. Join a new generation of mathematical scientists ready for leadership roles in education, industry, government laboratories, technology companies, and more.

This program is STEM designated, allowing international students who hold F-1 visas to apply for OPT work authorizations for a total of 36 months (an initial 1-year period and a 24-month OPT STEM extension) of paid work experience in the U.S. after graduation.

Program At a Glance

32 units

2 years

*This estimate assumes full-time registration and pursuit of the degree. Actual completion times will vary and may be higher, depending on full- or part-time course registration, units transferred, and time to complete other degree requirements.

Fall | Spring

MS in Computational & Applied Mathematics

Featured Courses

MATH 294
Methods of Applied Mathematics

Studies derivation of classical equations of applied math including quasilinear hyperbolic equations, Laplace, Poisson and Helmholtz equations, among others, in various orthogonal curvilinear coordinate systems.

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 362
Numerical Methods for Differential Equations

Studies numerical integration of ordinary and partial differential equations through methods such as Runge-Kutta and Adams formulas and more.

Math 462
Mathematics of Machine Learning

Covers theoretical foundations, algorithms, and methodologies for machine learning, emphasizing the role of probability and optimization and exploring a variety of real-world applications.

MATH 256
Stochastic Processes

Analyzes properties of independent and dependent random variables and examines conditional expectation among topics chosen from Markov processes and others.

MATH 306

Emphasizes nonlinear programming and numerical methods for finite-dimensional optimization problems with fairly smooth functions.

View all Mathematics Courses


Degree Requirements
A minimum of eight courses (32 units) of graduate math coursework is required, at least five of which (20 units) must be at the 300-level or higher.

Students who lack the prerequisite undergraduate coursework may be asked to complete more than 32 units. At least 20 units of coursework must be gamma courses (300-level and above). A grade of B- or above must be earned in gamma courses.

Students in the master’s program in mathematics, computational and applied mathematics, and statistical sciences may convert one 200-level (beta) course to gamma credit. At the discretion of the IMS Director, in consultation with the student’s academic advisor, more than one conversion may be approved in exceptional cases.

Core Courses (Four courses – 16 units)
Must include 4 of the following core courses:

  • Math 306 Optimization
  • Math 362 Numerical Methods for Differential Equations
  • Math 368 Numerical Methods for Matrix Computations
  • Math 387 Discrete Mathematical Modeling
  • Math 388 Continuous Mathematical Modeling
  • Math 462 Mathematics of Machine Learning

Restricted Electives
2 restricted electives can be chosen from either the list of core courses, or the following list (not all these courses are offered every year):

  • Math 256 Stochastic Processes
  • Math 293-393 Mathematics Clinic
  • Math 294 Methods of Applied Mathematics
  • Math 354 Reliability Theory
  • Math 357 Deterministic and Stochastic Control
  • Math 358 Mathematical Finance
  • Math 359 Computational Statistics
  • Math 381 Fluid Dynamics
  • Math 382 Perturbation and Asymptotic Analysis
  • Math 384 Advanced Partial Differential Equations
  • Math 385 Mathematical Modeling in Biology
  • Math 386 Image Processing
  • Math 389 Advanced Topics in Mathematics (if appropriate, with advisor’s approval)

Independent Study
In lieu of one formal course, students may take Math 398 Independent Study with a research advisor leading to a publication quality technical report in an area of computational or applied math.

Subject to approval by their academic advisor, students working outside campus on mathematical/statistical projects may also use this professional experience as the basis of a Math 398 Independent Study. At most 2 units per semester can be acquired in this practical type of independent study, which will not be counted as a gamma course.

Accelerated Degree Option

If you are an undergraduate student at the Claremont Colleges (Pomona, Scripps, Claremont McKenna, Harvey Mudd, Pitzer), you can obtain a graduate degree on an accelerated track through the Claremont Graduate Scholars Program, working toward your master’s requirements simultaneously with the completion of your undergraduate degree. Up to 16 units of transferable credit can be earned upon admission to one of our master’s degree programs. You are eligible for a minimum fellowship award of $5,000 per semester at CGU, based on 12 units of enrollment. Learn how to apply

Consider this opportunity if:

  • Your longer-term plans include a PhD in a math-related field (e.g. physics, engineering, computer science)
  • You are seeking a teaching career in math or science
  • You would like to get involved in ongoing research with CGU Math faculty during your senior year
  • You would like to earn your Master’s degree in half the usual time


Engineering & Computational Mathematics Clinic
CGU’s internationally recognized Engineering & Computational Mathematics Clinic offers first-hand experience solving significant mathematical problems for industry and government clients.

Recent projects include:

  • Optimizing Transmission of Renewable Energy–Southern California Edison
  • Hardware-Software Codesign–Los Alamos National Laboratory
  • Data Cohort Analysis–Fair Isaac
  • Optimizing Smart Power Grids–Los Alamos National Laboratory
  • Credit Risk in a Network Economy–Fitch Rating
  • Isogeometric Analysis–Boeing
  • Gate to Base Capacitance Modeling for Nanoscale MOSFETs–USC Information Sciences Institute
  • Practical Semi-Analytic Model for the Substrate Current of Short Channel MOSFETs with LDDs–USC Information Sciences Institute

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Claremont Center for the Mathematical Sciences
Through the Claremont Center for the Mathematical Sciences (CCMS), you’ll have access to one of the largest mathematical science communities in California, as well as to 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

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Faculty & Research

Extended Faculty

In addition to CGU core faculty, you will have access to Math faculty across the Claremont Colleges, including Pomona, Scripps, Harvey Mudd, Claremont McKenna, Pitzer, and Keck Graduate Institute, as well as faculty who are part of the W.M. Keck integrated science department.

View Full Faculty List

Harvey Mudd
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Claremont McKenna
View Math Faculty

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Bahar Acu
David Bachman
Jemma Lorenat

W.M. Keck Integrated Science Department
(Claremont McKenna, Pitzer, Scripps)
Adam Landsberg
John Milton

Keck Graduate Institute
Animesh Ray
James Sterling

Where You Can Find Our Alumni

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