Chairperson: Anne Clough, Ph.D.
Program Director: Mehdi Maadooliat, Ph.D.
Computational Sciences website
Doctor of Philosophy
Computational mathematical and statistical sciences (CMPS) is a field of study that emphasizes the discovery, implementation and use of computational tools to solve problems in mathematics and statistics that are both applied and pure. The master's degree program accommodates students whose objectives are either the master's degree or the preparation for doctoral study. The doctoral program is designed for individuals of outstanding ability who show promise as researchers in an interdisciplinary environment.
The diverse research opportunities in our graduate program are enhanced by the research faculty around Marquette's campus in the sciences and engineering and by the Milwaukee area research laboratories and clinics. Consult the Department of Mathematical and Statistical Sciences website for the most current information.
Computational Mathematical and Statistical Sciences Doctorate
A doctoral student in computational mathematical and statistical sciences must first complete a plan of study, designed to see the student through completion of the comprehensive examination. This plan of study should be prepared in cooperation with an adviser and approved by the Graduate Committee of the Department of Mathematical and Statistical Sciences.
Upon completion of the comprehensive examination, a doctoral student must then complete a program of study designed to see the student through completion of the program. This program of study should be defined, in cooperation with an adviser, on a Doctoral Program Planning Form and approved by the department's Graduate Committee.
The total 57-credit program includes a minimum of 45 credit hours of approved course work beyond the bachelor's degree plus 12 dissertation credits. Students must complete:
- the 15 credit hour core.
- a 3 credit hour adviser-approved COSC course.
- the 2 credit hours of MSSC 6090 Research Methods/Professional Development.
- at least 25 credit hours of electives. Approved programs of study normally include 6 credits of courses outside the department and no more than 12 credit hours in courses at the 5000 level.
- the 12 credit hours of MSSC 8999 Doctoral Dissertation.
Advancement to candidacy for the doctoral degree is considered after successful completion of the comprehensive examination, completion of all course work specified in the Doctoral Program Planning Form and successful completion of the qualifying examination, conducted by the student's doctoral committee. Typically, the doctoral committee also serves as the dissertation committee.
A full-time doctoral student is expected to complete the core courses within the first two years of study, and to take the comprehensive examination at the first opportunity after their completion. A student who enters the program with the necessary core courses is expected to take the comprehensive exam at the first available time it is offered.
|Required 15 credit hour core:|
|MSSC 6000||Scientific Computing||3|
|MSSC 6010||Computational Probability||3|
|MSSC 6020||Statistical Simulation||3|
|MSSC 6030||Applied Mathematical Analysis||3|
|MSSC 6040||Applied Linear Algebra||3|
|Choose an adviser-approved COSC 6000-6899 course||3|
|MSSC 6090||Research Methods/Professional Development (1 credit, taken at least twice)||2|
|Elective courses (no more than 12 credits at the 5000 level)||25|
|The Teaching of Mathematics|
|Concepts in Geometry and Calculus from an Advanced Standpoint|
|Concepts in High School Algebra and Number Theory from an Advanced Standpoint|
|Abstract Algebra 1|
|Abstract Algebra 2|
|Intermediate Analysis 1|
|Intermediate Analysis 2|
|History of Mathematical Ideas|
|Theory of Numbers|
|Foundations of Geometry|
|Theory of Differential Equations|
|Elementary Partial Differential Equations|
|Mathematical Modeling and Analysis|
|Theory of Optimization|
|Applied Combinatorial Mathematics|
|Theory of Probability|
|Introduction to R for Statistics and Data Science|
|Biostatistical Methods and Models|
|Time Series Analysis|
|Statistical Machine Vision|
|Topics in Mathematical or Statistical Sciences|
|Applied Discrete Mathematics|
|Theory of Statistics|
|Analysis of Variance and Covariance|
|Multivariate Statistical Analysis|
|Design and Analysis of Scientific Experiments|
|Statistical Machine Learning|
|Logic and Set Theory|
|Innovations in Secondary Mathematics: Meeting the NCTM Standards|
|Topics in Mathematical or Statistical Sciences|
Specific additional courses as approved by adviser in BIEN, COSC and EECE.
|MSSC 8999||Doctoral Dissertation||12|
|Total Credit Hours:||57|
All newly admitted computational mathematical and statistical sciences (CMPS) doctoral students who begin the program without an earned master’s degree in an acceptable field are simultaneously enrolled in the CMPS master of science program or the applied statistics (APST) master of science program as a Plan B student. These students concurrently complete both the master's degree of choice and the doctoral degree as part of the doctoral course of study.
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