
Mathematics Doctoral Program
Develop and conduct original, cutting-edge mathematical research that applies directly to real-world challenges with a Ph.D. in mathematics from Stevens.
Here, you’ll enhance your expertise in mathematics foundations and complex mathematical models, but you’ll also learn how to effectively communicate that expertise through presentations and seminars. Alongside a faculty mentor you choose from among our world-class experts, you’ll produce a dissertation that develops a significant result in mathematics, as well as its application. You’ll graduate from the program well prepared for professorial and postdoctoral positions but also leadership roles in various industries, such as government and military research, scientific and management consulting, pharmaceuticals, insurance and financial services.
The Department of Mathematical Sciences offers dynamic opportunities to explore leading-edge research within a close community of faculty mentors. You'll be able to study under a faculty mentor in the area that you find most exciting:
Risk-Averse Optimization
Statistics
Statistical Learning
Design of Clinical Trials
Portfolio Theory
PDES in Application to Fluid Mechanics
Inverse Problems in Science and Engineering
Group Theory
Algebraic Cryptography
Quantum Algorithms
Graph Theory
Mathematical Sciences Research at Stevens
Major advantages of studying mathematical sciences at a premier research institution like Stevens include support for your ideas, great mentors and the best tools for your research. Learn more about research in the Department of Mathematical Sciences.
The Stevens Advantage
Stevens’ Hoboken, N.J., campus is located close to numerous industry hubs—such as the pharmaceutical corridor in New Jersey and epicenter of American finance in Manhattan—as well as a thriving start-up ecosystem. Employers in these sectors are always on the lookout for talented graduates with expertise in mathematics.
More Advantages to Our Program
Customizable curriculum based on student’s needs and interests
Rigorous coursework involving training in foundational mathematics
Advanced research opportunities working with recognized experts in the field
Interdisciplinary electives and independent study
Collaboration with other universities and experience working in or with national research centers
Career-building activities outside of the classroom, such as professional seminars that students may attend and/or organize
Additional Information
Who Should Apply?
We welcome applicants who hold a master’s degree in mathematics, applied mathematics, or computer science (up to 30 credits may transfer to the Stevens Ph.D. program). Exceptionally well-qualified applicants with a bachelor’s degree in these fields who have demonstrated a solid mathematical and analytical orientation may apply directly to the doctoral program instead of the master’s program.
We strongly advise applying for fall semester because of (a) the constraints of course scheduling and (b) the availability of financial aid. You should submit your application by February 15 for the following fall.
Applications must be received by February 15 if an applicant wishes to be considered for financial aid. A limited number of Ph.D. students may receive teaching assistantships, which provide recipients with a salary and waiver of tuition costs.
Program Admission Requirements
Bachelor’s degree, with a minimum GPA of 3.0, from an accredited institution
Official college transcripts. For non-English-speaking institutions, these documents must be accompanied by a certified English translation.
Two to four letters of recommendation
Resume or curriculum vitae
A two page personal statement describes the student’s reasons for pursuing a Ph.D., prior classroom and research experience in mathematics, current mathematical interests, and whether or not you wish to be considered for a teaching assistantship
For international students: An excellent TOEFL/IELTS score
A competitive GRE or GMAT score (Math Subject Test recommended) (required for both part-time and full-time applicants)
For information about fellowships and assistantships, contact Graduate Admissions. Contact >
Pure and Applied Mathematics Doctoral Program Curriculum Overview
The doctoral program provides opportunity to gain deep expertise, conduct research and write a thesis in the areas of stochastic modeling, optimization, graph theory, group theory, cryptography, probability, and mathematical finance under the guidance of world-class experts. Its main outcome is producing an original and significant result in mathematics and its application. In addition to rigorous coursework, doctoral candidates are expected to explore and learn on their own outside of class, e.g., by attending and organizing seminars.
By the end of this program, you will be able to:
Take leadership and initiative in scientific projects and devise research programs related to their areas of expertise
Develop mathematical models within their areas of expertise, explain the underlying assumptions that were used in constructing a model, and understand the limitations of a particular model
Identify and apply appropriate analytical and numerical methodologies for investigating a model and develop and implement suitable numerical algorithms, as needed
Effectively communicate mathematical concepts and results and use reasoned arguments to defend those results through both written reports and oral presentations
Teach undergraduate and graduate-level courses within their areas of expertise
Serve as referees for scientific work and proposals relevant to their areas of expertise
Degree Requirements
The doctoral program requires 84 credits beyond the bachelor’s degree (54 credits beyond the master’s) of which at least 30 credits must be doctoral research credits (MA 960). This credit total includes the three-credit “Signature” course, PRV961. Some of the 30 research credits can be substituted by course credits with approval from the thesis advisor. A prior master’s degree may be transferred for up to 30 credits without specific course descriptions and with approval of the department and the Dean of Graduate Academics. Up to one-third of additional course credits may be transferred with the approval of the thesis committee and the Dean of Graduate Academics. The grade of “B” (3.0 GPA) or better is required for such courses and such courses may not have been already used to obtain an academic degree. The preliminary requirements for the doctorate are regarded not as ends in themselves, but rather as preparation for the dissertation in which the student demonstrates ability.
Qualifying Examination
The general (qualifying) exam tests the knowledge of three subjects: real analysis and two subjects chosen in consultation with the student’s academic advisor. The real analysis subject is based on two courses: Real Variables I and II (MA 635, MA 636), and each chosen subject is based on two closely related courses. Subjects and corresponding courses include but are not limited to:
Algebra: Foundations of Algebra I and II (MA 605, MA 606)
Discrete Mathematics: Combinatorial Analysis (MA 627) and Introduction to Network & Graph Theory (MA 620)
ODEs and Numerical Analysis: Numerical Analysis (MA 615) and Intermediate Differential Equations (MA 649)
Optimization: Nonlinear Optimization (MA 629) and either Advanced Optimization Methods (MA 630) or Dynamic Programming & Reinforcement Learning (MA 661) or Stochastic Optimization (MA 662) or Optimal Control (MA 655)
PDEs & Complex Analysis: Partial Differential Equations (MA 650) and either Functions of a Complex Variable I (MA 681) or Numerical Solutions of PDEs (MA 653) or Inverse Problems in Science and Engineering (MA 711)
Probability & Statistics: Probability (MA 611) and either Mathematical Statistics (MA 612) or Stochastic Processes (MA 623) or Time Series Analysis I (MA 641) or Multivariate Statistics (MA 720)
A student and his/her academic advisor can propose different course combinations for the above subjects or propose other subjects along with corresponding courses. Such proposals must be submitted to the graduate committee for approval three months prior to taking the qualifying exam. Students admitted to the Ph.D. program with BS/MS degrees should attempt the qualifying exam no later than the end of their fourth/second semester.
Students pass the qualifying exam and are admitted to Ph.D. candidacy if they score at least 70 out of 100 on each subject. Students failing all three subjects will not be admitted to Ph.D. candidacy. Students failing at most two subjects are allowed a second attempt to pass exams on the failed subjects. This second attempt is to take place in the following semester. Students are admitted to Ph.D. candidacy only if they pass all remaining subjects on the second attempt.
Doctoral Dissertation and Advisory Committee
The primary requirement for a doctoral degree in mathematics is that you produce a dissertation containing an original and significant result in mathematics. You will work under the guidance of a faculty advisor who is an expert in your area of research.
Preparation for dissertation work includes both courses in mathematical fundamentals and practice in communicating mathematics orally and in writing. The courses you take will not necessarily include everything you will need to know. As a doctoral student you will be expected to learn some mathematics on your own outside of class. Seminars afford a means to that end. They can be organized informally among students or more formally with a faculty advisor. Seminars of the latter type may be taken for academic credit. Students are encouraged to identify subjects they would like to study and to seek out faculty advisors.
LEARN MORE ABOUT GENERAL REQUIREMENTS >
If you have existing graduate credits or experience in this area of study, please contact [email protected] to discuss opportunities to include it in the curriculum.
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