Degree Programs

* M.S. Degree Program Guidelines [PDF version] [Postscript version]
* M.S. Plan of Study Worksheet [PDF version] [Postscript version]
* M.S. Project Guidelines [PDF version] [Postscript version]
* Mathematical Sciences PhD Program Guidelines [PDF version] [Postscript version]
* [ Web Page for PhD Program in Management Science]

Admission

The admission decision is based upon grades in previous degree programs, GRE scores (advanced test not required), letters of recommendation, and TOEFL scores (for non-English speaking students). Applications are accepted throughout the year, but applicants are encouraged to apply prior to February of each year. Only complete applications are considered. Selection for financial aid is more competitive than just admission to the department. The most important criterion for admission is whether a student's background and ability are sufficient to expect successful completion of the degree program. The Graduate School generally requires a minimum 3.0 GPR and 1500 GRE (v+q+a) score for admission with full status.

Advising

Every incoming student is assigned an initial adviser based on the student's stated area of interest. This adviser assists the student in the development of an initial plan of study. Because of the diversity in the department's course offerings, the initial plans of study are intended to give a student maximum flexibility in choosing an area of concentration - a decision which is not required until the end of the first year of study. During the second semester of study (MS) or upon completion of the qualifying examination (PhD), students are encouraged to find an adviser of their own choosing.

Master's Degree

The master's degree program requires breadth of exposure in the mathematical sciences and depth of concentration in one particular area. For breadth, each student selects courses to satisfy certain distributional requirements across the spectrum of mathematical sciences. For depth, each student, in consultation with a faculty adviser, chooses six courses which comprise a meaningful concentration in some specialty within the mathematical sciences. Each student's overall program must contain courses with a significant modeling component.

Entering students are expected to have undergraduate courses in linear algebra, differential equations, a computer language, and statistics. The curriculum includes foundation courses (advanced calculus, modern algebra, probability, and discrete computing courses often taken prior to entering the master's program); a breadth requirement (a graduate course from each of algebra/combinatorics, analysis, computing, operations research, and statistics plus one additional course in operations research or statistics); and a concentration area (six courses selected to define an identifiable specialty area). Every student's program is required to include at least one course, possibly chosen from outside the Department of Mathematical Sciences, which emphasizes mathematical modeling. As a means of integrating the student's program of diverse study, a master's project must be completed by the end of the second year. The student makes an oral and written presentation of the master's degree project.

A faculty adviser is assigned to every incoming student prior to preregistration for the first semester of enrollment. Each student chooses an adviser and master's committee during the second semester. A minimum of 36 graduate hours plus the one-credit-hour project course is required for the master's degree. Typical MS programs total 40 hours.

Doctoral Degree

The doctoral program is similar in structure to the MS program in that it has both breadth and depth components. Including master's study, a doctoral program incorporates two courses from each of the major areas of the mathematical sciences (algebra/combinatorics, analysis, computation, operations research, and statistics) and a concentration area. A doctoral program generally consists of 60 or more hours of graduate coursework.

Students are admitted to candidacy for the PhD degree upon successful completion of a qualifying examination consisting of three tests chosen from any of the areas of algebra, analysis, computing, operations research, statistics, or stochastic processes. Upon completion of the qualifying examination, the student chooses a research committee and adviser and submits a plan of study. A comprehensive examination, usually including a thesis proposal, is administered by the student's advisory committee. A final examination is administered by that committee prior to receipt of the doctoral degree.

The PhD program in Mathematical Sciences structures the five areas of the mathematical sciences into three disciplines: applied and computational analysis, discrete mathematics, and probability and statistics. Doctoral research culminating in a dissertation within each discipline may range from topics having a strong modeling component to those that are strictly theoretical. A student's PhD program must include both a concentration area and a supporting area. Further descriptions of these areas are given below.

Applied and Computational Analysis

The discipline of applied and computational analysis encompasses the study of dynamical systems (ordinary, integral, partial differential equations), numerical analysis, functional analysis, and harmonic analysis. Research topics within this discipline are closely related to problems which arise in engineering, economics, and the biological sciences. A plan of study within this discipline will emphasize courses in theoretical analysis, dynamical systems, numerical analysis, and physical system modeling.

Discrete Mathematics

The discipline of discrete mathematics encompasses algebra, combinatorics/graph theory, computational mathematics, and operations research. Research topics include algebraic structures, algorithms, combinatorial optimization, discrete computing, graph theory, mathematical programming, matrix theory, and networks - emphasizing the interdisciplinary and broad-based nature of this discipline.

Statistics and Probability

The discipline of statistics and probability encompasses mathematical statistics, statistical methodology/data analysis, and stochastic models. These three comprise the core upon which research progress in statistical theory and methods is based.

Management Science PhD Program

The Departments of Management and Mathematical Sciences jointly offer and administer a doctoral program in Management Science. Information on that program can be obtained by writing the Management Science Program Coordinator in either the Department of Management or the Department of Mathematical Sciences.