The Mathematical Sciences Department at The University of Texas at Dallas offers graduate study in six majors: actuarial science, applied mathematics, engineering mathematics, mathematics, statistics, and an interdisciplinary degree in Bioinformatics and Computational biology. The degree programs offer students the opportunity to prepare for careers in these disciplines themselves or in any of the many other fields for which these disciplines are such indispensable tools. As other sciences develop, problems which require the use of these tools are numerous and pressing.
In addition to a wide range of courses in mathematics and statistics, the Mathematical Sciences Department offers a unique selection of courses that consider mathematical and computational aspects of engineering, biology, and other scientific problems.
The Master of Science degree programs are designed for persons seeking specializations in actuarial science, applied mathematics, engineering mathematics, mathematics, statistics, bioinformatics and computational biology.
The Master of Science degree is available also for those who plan to teach mathematical sciences above the remedial level at a community college or at a college or university. The Master of Science degree is recommended as a minimum, since an earned doctorate is sometimes required.
For information concerning the Master of Arts in Teaching in Mathematics Education, designed for persons who are teaching in grades 6-12, see the Department of Science/Mathematics Education.
The Doctor of Philosophy degree programs cover two basic areas of concentration: statistics and applied mathematics. They are designed for those who plan to pursue academic, financial or industrial careers.
The mission of the Master’s program in Bioinformatics and Computational Biology is to provide students with strong knowledge of mathematical theory and its application to bioinformatics and biology, The goal of the program is to prepare students for competitive in fields related to bioinformatics for industry, medical and biological research, and government agencies.
The mission of the Master’s program in Mathematics and Applied Mathematics is to provide students with strong knowledge of mathematical theory and its application to a broad range of fields, The goal of the program is to prepare students for competitive in mathematics, applied mathematics, and related fields for industry and government agencies.
The mission of the Doctoral program in Applied Mathematics is to provide students with strong knowledge of mathematical theory and its application to a broad range of fields, ability to conduct independent research in theoretical and applied areas of Mathematics. The goal of the program is to prepare students for competitive research-oriented positions in mathematics, applied mathematics, and related fields for industry, government agencies, and universities.
The mission of the MS program in Actuarial Science is to educate future leaders of the actuarial industry with training in actuarial theory and methods in a wide spectrum of actuarial applications involving probabilistic and statistical models. All students will be prepared to take five actuarial preliminary exams and will take two advanced actuarial classes to prepare for professional accreditation. With this combined knowledge of mathematics particularly of probability, statistics, and decision theory together with knowledge of financial mathematics and insurance, the expected passing of five actuarial exams, and the three required VEE credits, graduates of the program will be able to work as senior actuaries in insurance, consulting, finance, government, and emerging markets.
Within the Mathematical Sciences program opportunities exist for work and/or research in actuarial science, applied mathematics, engineering mathematics, mathematics and statistics. The opportunity to take course work in several of the other university programs also allows the student to prepare for interdisciplinary work. Special topics within research areas include functional analysis, operator theory, differential and integral equations, optimization, numerical analysis, system theory and control with application in material and molecular sciences, inverse problems with applications in geosciences and medical sciences, relativistic cosmology, differential geometry, applications of topology to biology, mathematical and computational biology with applications in cardiovascular physiology, neurobiology and cell biology; probability theory, applied probability, stochastic processes, mathematical statistics, statistical inference, asymptotic theory, statistical time series, Bayesian analysis, robust multivariate statistical methods, robust linear models, robust and nonparametric methods, sequential analysis, statistical computing, signal processing, remote sensing, change-point problems, forecasting and applications in their respective areas such as energy finance, semiconductor manufacturing, psychology, actuarial sciences, physical and medical sciences.
- Updated: February 10, 2015