Applied and Computational Mathematics Master of Science Degree

An applied and computational mathematics master’s degree that is designed for you to create innovative computing solutions, mathematical models, and dynamic systems to solve problems in industries such as engineering, biology, and more.


100%

Outcome Rate of RIT Graduates

$65.3K

Average First-Year Salary of RIT Graduates

30%

Merit scholarship

Average award given to accepted students

Overview

  • Apply mathematical models and methods to study various problems that arise in industry and business, with an emphasis on developing computable solutions.
  • Work in areas such as mathematical modeling and analysis of manufacturing, computer and communications systems, transportation optimization, financial mathematics, biological modeling, and consulting/planning.
  • Current program research includes network science, image analysis, contact lens, polymeric flows, coating, lake plastic, climate modeling, relativity, multi-messenger astrophysics, data analytics, and machine learning.
  • Apple, BAE Systems, Ernst & Young, IBM, and Microsoft are just a sampling of employers who hire graduates from the applied and computational mathematics program.

The applied and computational mathematics master’s degree refines your capabilities in applying mathematical models and methods to study a range of problems, with an emphasis on developing and implementing computing solutions. Sophisticated mathematical tools are increasingly used to solve problems in management science, engineering, biology, financial portfolio planning, facilities planning, control of dynamic systems, and design of composite materials. The goal of RIT’s master's in applied mathematics is to find computing solutions to real-world problems.

Applied and Computational Mathematics

The ideas of applied mathematics pervade several applications in a variety of businesses and industries as well as the government. The reasoning, deduction, and logic skills developed in this program will make you more competitive in a wide array of positions and industries.

Sophisticated mathematical tools are increasingly used to develop new models, modify existing ones, and analyze system performance. This includes applications of mathematics to problems in management science, biology, portfolio planning, facilities planning, control of dynamic systems, and design of composite materials. The goal of this mathematics master's degree is to find computable solutions to real-world problems arising from these types of situations.

RIT’s Master’s in Applied Mathematics

RIT's mathematics master's provides you with the capability to apply mathematical models and methods to study various problems that arise in industry and business, with an emphasis on developing computable solutions that can be implemented.

Tailor the applied and computational mathematics master’s degree to fit your career goals. Electives may be selected from the graduate course offerings in the School of Mathematical Sciences or from other RIT graduate programs, with approval from the graduate program director. You also have the option to complete a thesis, which includes the presentation of original ideas and solutions to a specific mathematical problem. The proposal for the thesis work and the results must be presented and defended before the advisory committee.

Applied Mathematics Careers

Graduates of the masters in applied mathematics are uniquely qualified to address the full breadth of mathematical challenges and have developed a depth of knowledge in their chosen specializations.

The Department of Defense accounts for about 81 percent of the mathematicians employed by the federal government. In the private sector, mathematicians are employed by scientific research and development services, software publishers, insurance companies, and in aerospace or pharmaceutical manufacturing.

Recent graduates are employed as engineers, economists, analysts (e.g. operations research), physicists, cryptanalysts (codes), actuaries, teachers, market researchers, and financial advisors. Apple, BAE Systems, Ernst & Young, IBM, and Microsoft are just a few of the employers who have hired graduates of the applied and computational mathematics program.

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Careers and Experiential Learning

Typical Job Titles

Network Consulting Engineer Junior Accountant
Data Analyst Software Engineer
Junior Business Analyst Data Scientist
Technical Advisory Fund Accountant
Sr. Project Manager

Salary and Career Information for Applied and Computational Mathematics MS

Cooperative Education

What makes an RIT science and math education exceptional? It’s the ability to complete science and math co-ops and gain real-world experience that sets you apart. Co-ops in the College of Science include cooperative education and internship experiences in industry and health care settings, as well as research in an academic, industry, or national lab. These are not only possible at RIT, but are passionately encouraged.

What makes an RIT education exceptional? It’s the ability to complete relevant, hands-on career experience. At the graduate level, and paired with an advanced degree, cooperative education and internships give you the unparalleled credentials that truly set you apart. Learn more about graduate co-op and how it provides you with the career experience employers look for in their next top hires.

National Labs Career Fair

Hosted by RIT’s Office of Career Services and Cooperative Education, the National Labs Career Fair is an annual event that brings representatives to campus from the United States’ federally funded research and development labs. These national labs focus on scientific discovery, clean energy development, national security, technology advancements, and more. Students are invited to attend the career fair to network with lab professionals, learn about opportunities, and interview for co-ops, internships, research positions, and full-time employment.

Featured Profiles

Curriculum for Applied and Computational Mathematics MS

Applied and Computational Mathematics (thesis option), MS degree, typical course sequence

Course Sem. Cr. Hrs.
First Year
Choose three of the following core courses: 9
   MATH-601
   Methods of Applied Mathematics 
This course is an introduction to classical techniques used in applied mathematics. Models arising in physics and engineering are introduced. Topics include dimensional analysis, scaling techniques, regular and singular perturbation theory, and calculus of variations. (Prerequisites: MATH-221 and MATH-231 or equivalent courses or students in the ACMTH-MS or MATHML-PHD programs.) Lecture 3 (Spring).
 
   MATH-602
   Numerical Analysis I 
This course covers numerical techniques for the solution of nonlinear equations, interpolation, differentiation, integration, and matrix algebra. (Prerequisites: ((MATH-241 or MATH-241H) and MATH-431) or equivalent courses or graduate standing in ACMTH-MS or MATHML-PHD programs.) Lecture 3 (Fall).
 
   MATH-605
   Stochastic Processes
This course is an introduction to stochastic processes and their various applications. It covers the development of basic properties and applications of Poisson processes and Markov chains in discrete and continuous time. Extensive use is made of conditional probability and conditional expectation. Further topics such as renewal processes, reliability and Brownian motion may be discussed as time allows. (Prerequisites: ((MATH-241 or MATH-241H) and MATH-251) or equivalent courses or graduate standing in ACMTH-MS or MATHML-PHD or APPSTAT-MS programs.) Lecture 3 (Spring).
 
   MATH-622
   Mathematical Modeling I
This course will introduce graduate students to the logical methodology of mathematical modeling. They will learn how to use an application field problem as a standard for defining equations that can be used to solve that problem, how to establish a nested hierarchy of models for an application field problem in order to clarify the problem’s context and facilitate its solution. Students will also learn how mathematical theory, closed-form solutions for special cases, and computational methods should be integrated into the modeling process in order to provide insight into application fields and solutions to particular problems. Students will study principles of model verification and validation, parameter identification and parameter sensitivity and their roles in mathematical modeling. In addition, students will be introduced to particular mathematical models of various types: stochastic models, PDE models, dynamical system models, graph-theoretic models, algebraic models, and perhaps other types of models. They will use these models to exemplify the broad principles and methods that they will learn in this course, and they will use these models to build up a stock of models that they can call upon as examples of good modeling practice. (This course is restricted to students in the ACMTH-MS or MATHML-PHD programs.) Lecture 3 (Fall).
 
   MATH-645
   Graph Theory
This course introduces the fundamental concepts of graph theory. Topics to be studied include graph isomorphism, trees, network flows, connectivity in graphs, matchings, graph colorings, and planar graphs. Applications such as traffic routing and scheduling problems will be considered. (This course is restricted to students with graduate standing in the College of Science or Graduate Computing and Information Sciences.) Lecture 3 (Fall).
 
   MATH-722
   Mathematical Modeling II
This course will continue to expose students to the logical methodology of mathematical modeling. It will also provide them with numerous examples of mathematical models from various fields. (Prerequisite: MATH-622 or equivalent course.) Lecture 3 (Spring).
 
MATH-606
Graduate Seminar I
The course prepares students to engage in activities necessary for independent mathematical research and introduces students to a broad range of active interdisciplinary programs related to applied mathematics. (This course is restricted to students in the ACMTH-MS or MATHML-PHD programs.) Lecture 2 (Fall).
1
MATH-607
Graduate Seminar II
This course is a continuation of Graduate Seminar I. It prepares students to engage in activities necessary for independent mathematical research and introduces them to a broad range of active interdisciplinary programs related to applied mathematics. (Prerequisite: MATH-606 or equivalent course or students in the ACMTH-MS or MATHML-PHD programs.) Lecture 2 (Spring).
1
 
MATH Graduate Electives
9
Second Year
MATH-790
Research & Thesis
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. (This course is restricted to students in the ACMTH-MS or MATHML-PHD programs.) Thesis (Fall, Spring, Summer).
7
 
MATH Graduate Elective
3
Total Semester Credit Hours
30

Applied and Computational Mathematics (project option), MS degree, typical course sequence

Course Sem. Cr. Hrs.
First Year
Choose three of the following core courses:
9
   MATH-601
   Methods of Applied Mathematics
This course is an introduction to classical techniques used in applied mathematics. Models arising in physics and engineering are introduced. Topics include dimensional analysis, scaling techniques, regular and singular perturbation theory, and calculus of variations. (Prerequisites: MATH-221 and MATH-231 or equivalent courses or students in the ACMTH-MS or MATHML-PHD programs.) Lecture 3 (Spring).
 
   MATH-602
   Numerical Analysis I
This course covers numerical techniques for the solution of nonlinear equations, interpolation, differentiation, integration, and matrix algebra. (Prerequisites: ((MATH-241 or MATH-241H) and MATH-431) or equivalent courses or graduate standing in ACMTH-MS or MATHML-PHD programs.) Lecture 3 (Fall).
 
   MATH-605
   Stochastic Processes
This course is an introduction to stochastic processes and their various applications. It covers the development of basic properties and applications of Poisson processes and Markov chains in discrete and continuous time. Extensive use is made of conditional probability and conditional expectation. Further topics such as renewal processes, reliability and Brownian motion may be discussed as time allows. (Prerequisites: ((MATH-241 or MATH-241H) and MATH-251) or equivalent courses or graduate standing in ACMTH-MS or MATHML-PHD or APPSTAT-MS programs.) Lecture 3 (Spring).
 
   MATH-622
   Mathematical Modeling I
This course will introduce graduate students to the logical methodology of mathematical modeling. They will learn how to use an application field problem as a standard for defining equations that can be used to solve that problem, how to establish a nested hierarchy of models for an application field problem in order to clarify the problem’s context and facilitate its solution. Students will also learn how mathematical theory, closed-form solutions for special cases, and computational methods should be integrated into the modeling process in order to provide insight into application fields and solutions to particular problems. Students will study principles of model verification and validation, parameter identification and parameter sensitivity and their roles in mathematical modeling. In addition, students will be introduced to particular mathematical models of various types: stochastic models, PDE models, dynamical system models, graph-theoretic models, algebraic models, and perhaps other types of models. They will use these models to exemplify the broad principles and methods that they will learn in this course, and they will use these models to build up a stock of models that they can call upon as examples of good modeling practice. (This course is restricted to students in the ACMTH-MS or MATHML-PHD programs.) Lecture 3 (Fall).
 
   MATH-645
   Graph Theory
This course introduces the fundamental concepts of graph theory. Topics to be studied include graph isomorphism, trees, network flows, connectivity in graphs, matchings, graph colorings, and planar graphs. Applications such as traffic routing and scheduling problems will be considered. (This course is restricted to students with graduate standing in the College of Science or Graduate Computing and Information Sciences.) Lecture 3 (Fall).
 
   MATH-722
   Mathematical Modeling II
This course will continue to expose students to the logical methodology of mathematical modeling. It will also provide them with numerous examples of mathematical models from various fields. (Prerequisite: MATH-622 or equivalent course.) Lecture 3 (Spring).
 
MATH-606
Graduate Seminar I
The course prepares students to engage in activities necessary for independent mathematical research and introduces students to a broad range of active interdisciplinary programs related to applied mathematics. (This course is restricted to students in the ACMTH-MS or MATHML-PHD programs.) Lecture 2 (Fall).
1
MATH-607
Graduate Seminar II
This course is a continuation of Graduate Seminar I. It prepares students to engage in activities necessary for independent mathematical research and introduces them to a broad range of active interdisciplinary programs related to applied mathematics. (Prerequisite: MATH-606 or equivalent course or students in the ACMTH-MS or MATHML-PHD programs.) Lecture 2 (Spring).
1
 
MATH Graduate Electives
9
Second Year
MATH-790
Research & Thesis
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. (This course is restricted to students in the ACMTH-MS or MATHML-PHD programs.) Thesis (Fall, Spring, Summer).
4
 
MATH Graduate Electives
6
Total Semester Credit Hours
30

Admission Requirements

To be considered for admission to the MS program in applied and computational mathematics, candidates must fulfill the following requirements:

  • Complete an online graduate application. Refer to Graduate Admission Deadlines and Requirements for information on application deadlines, entry terms, and more.
  • Submit copies of official transcript(s) (in English) of all previously completed undergraduate and graduate course work, including any transfer credit earned.
  • Hold a baccalaureate degree (or US equivalent) from an accredited university or college in mathematics or a related field.
  • Recommended minimum cumulative GPA of 3.0 (or equivalent).
  • Submit a current resume or curriculum vitae.
  • Two letters of recommendation are required. Refer to Application Instructions and Requirements for additional information.
  • Not all programs require the submission of scores from entrance exams (GMAT or GRE). Please refer to the Graduate Admission Deadlines and Requirements page for more information.
  • Submit a personal statement of educational objectives. Refer to Application Instructions and Requirements for additional information.
  • Have college level credit or practical experience in programming language.
  • International applicants whose native language is not English must submit official test scores from the TOEFL, IELTS, or PTE. Students below the minimum requirement may be considered for conditional admission. Refer to Graduate Admission Deadlines and Requirements for additional information on English language requirements. International applicants may be considered for an English test requirement waiver. Refer to the English Language Test Scores section within Graduate Application Materials to review waiver eligibility.

Although Graduate Record Examination (GRE) scores are not required, submitting them may enhance a candidate's acceptance into the program.

A student may also be granted conditional admission and be required to complete bridge courses selected from among RIT’s existing undergraduate courses, as prescribed by the student’s advisor. Until these requirements are met, the candidate is considered a nonmatriculated student. The graduate program director evaluates the student’s qualifications to determine eligibility for conditional and provisional admission.

Nonmatriculated students

A student with a bachelor’s degree from an approved undergraduate institution, and with the background necessary for specific courses, may take graduate courses as a nonmatriculated student with the permission of the graduate program director and the course instructor. Courses taken for credit may be applied toward the master’s degree if the student is formally admitted to the program at a later date. However, the number of credit hours that may be transferred into the program from courses taken at RIT is limited for nonmatriculated students.

Learn about admissions, cost, and financial aid 

Research

Students in the master's in applied mathematics program are engaged in research projects covering topics that include:

  • Bio modeling
  • Brain imaging
  • Climate modeling
  • Cryptography
  • Fluid flow
  • Machine learning
  • Oil recovery
  • Plastic pollution
  • Relativity

The School of Mathematical Science consistently receives research grant awards from organizations that include the National Science Foundation, National Institutes of Health, and NASA, which provide you with unique opportunities to conduct cutting-edge research with our faculty members. Faculty in the School of Mathematical Sciences conducts research on a broad variety of topics including:

  • applied inverse problems and optimization
  • applied statistics and data analytics
  • biomedical mathematics
  • discrete mathematics
  • dynamical systems and fluid dynamics
  • geometry, relativity, and gravitation
  • mathematics of earth and environment systems
  • multi-messenger and multi-wavelength astrophysics

Learn more by exploring the school's mathematics research areas.

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