**Description **

Our Master of Science in Applied Mathematics is intended to prepare students for a wide range of possible careers putting mathematics to work on real-world problems. The program is designed for flexibility to allow for the many possible directions applied mathematics careers can take. The possibilities range from industrial careers, to Ph.D. programs, or teaching in the Community College System. Local industry, including biotech, the U.S. Navy, HNC, SAIC and GA have lucrative positions available for our graduates. Students should assemble a specific program of study in consultation with an adviser to make sure that all of the coursework is appropriately aimed at the student’s specific career objectives.

To assist with advising, the student is expected to write a short description (100-200 words) concerning his or her particular interests and expectations from the program. Based on this description, an appropriate faculty member will be consulted to help design the student’s program. After the first year of study, the student should select a faculty member as an adviser for advanced study leading to a thesis. By the end of the first year the student should file an Official Program which has been approved by the graduate adviser.

**Faculty **

Ricardo Carretero – nonlinear dynamics, mathematical physics.

Jose Castillo – numerical analysis, computational fluid dynamics.

Jerome Gilles — applied harmonic analysis, data-driven methods for signal and image analysis, wavelets.

Joseph Mahaffy – modeling, biomathematics, time-delay differential equations.

Antonio Palacios — nonlinear dynamics, bifurcation theory, mathematical biology, mathematical physics.

Peter Salamon – modeling, optimization, thermodynamics, mathematical biology.

Toni Luque Santolaria ļ¼biomathematics, numerical methods, SDSU Area of Excellence in viral information.

Bo-Wen Shen — climate mathematics, SDSU Area of Excellence in Climate and Sustainability Studies.

Sam Shen – climate modeling, climate data analysis, nonlinear waves.

**Admission Requirements **

In preparation for the degree it is expected that the student has acquired a knowledge of the following course material: (SDSU course numbers shown)

Linear Algebra (524) 1 semester;

Advanced Calculus (534 A&B) 2 semesters;

Numerical Analysis (541) 1 semester;

Probability and/or Statistics (550 and/or 551A) 1 semester;

Programming proficiency on some platform;

Deficiencies may be made up, but they will not count toward the degree unit requirements. These deficiencies are to be completed within the first year unless scheduling difficulties make this impossible. It is also recommended that the student possess a background in several of the following areas:

Differential Equations (537 and 531);

Numerical Analysis (542);

Mathematical Modeling (336);

Optimization Theory (562);

Mathematical Statistics (55lB);

Complex Analysis (532);

Abstract Algebra (521A);

Field of application (Physics, Biology, Engineering, etc.)

The Department maintains a web page with further information on graduate admissions and financial support.

**Course Requirements**

Candidates must take 30 units of adviser approved upper division and graduate courses. All programs must include at least 21 units in Mathematical Sciences and at least 18 units selected from 600 and 700 number courses. At most, six units in Mathematics 797 and 798 will be accepted for credit toward the degree.

Most students are encouraged to take the core courses in Applied Mathematics: Mathematical Modeling (636), Optimization Theory (662), Numerical Analysis (542), and Mathematical Statistics (551B).

By the end of the first year, the student should select a faculty member and a thesis topic. The thesis requires about two courses worth of effort and most students enroll in Math 797 for the research portion prior to writing and defending the thesis. The student may be asked to enroll in a Technical Writing course or to show other evidence of proficiency in technical writing, if the adviser feels that this course is desirable.

Advisor: Dr. Sam Shen, sam.shen@sdsu.edu