Virginia Commonwealth University

What you'll study

The programme builds a strong foundation in pure and applied mathematics while emphasising computational methods and algorithmic thinking. Core coursework typically includes multivariable calculus, linear algebra, differential equations, mathematical proof and real analysis. Computational and applied components cover numerical analysis, scientific computing, numerical linear algebra, mathematical modelling, optimization and discrete mathematics.

Students also take programming-focused modules that teach languages and tools commonly used in scientific computing, such as Python, MATLAB and libraries for numerical work, together with courses in data analysis, probability and statistics. The curriculum is designed to blend theory with practice through lab-based assignments, coding projects, and a senior capstone or honours project where students implement numerical methods to solve real-world problems.

Electives allow specialisation in areas such as computational finance, stochastic processes, computational geometry, mathematical biology, or machine learning. The degree also integrates Virginia Commonwealth University's general education requirements, enabling breadth across the humanities and sciences and opportunities for interdisciplinary study with departments such as Computer Science, Engineering or the School of Business.

Entry requirements

Applicants should hold a high school diploma or equivalent with a strong background in mathematics. Typical preparation includes completion of algebra, geometry, trigonometry and preferably calculus at the high school level. Schools will look for evidence of analytical ability demonstrated through grades in maths courses and, where available, standardised test scores or placement assessments.

Familiarity with programming is advantageous but not always mandatory; students without prior coding experience are usually supported through introductory programming modules. International applicants must meet the university's English language requirements. Transfer students are considered with evaluation of prior college coursework in mathematics and related fields.

Career prospects

Graduates with a computational mathematics specialism are prepared for careers that require strong quantitative and computational skills. Common roles include data analyst, data scientist, software or algorithm developer, quantitative analyst in finance, and roles in computational modelling for engineering, biology or environmental science. Employers span private industry, government agencies, healthcare and finance, as well as technology and consulting firms.

The degree also provides solid preparation for graduate study in applied mathematics, computer science, statistics, engineering and related disciplines. Some graduates pursue professional paths in actuarial work, operations research, or continue into research and academic careers. Practical training, internship experiences and capstone projects help build a portfolio of applied work for job applications.

Why study at Virginia Commonwealth University

Virginia Commonwealth University offers the advantages of a large, urban public research university with access to interdisciplinary collaborations and applied research opportunities. Mathematics students benefit from hands-on computational training, access to campus computing resources and opportunities to work with faculty on research projects that intersect with engineering, biomedical sciences and data analytics.

The Richmond location supports internships and industry connections with local companies, healthcare institutions and public agencies, helping students gain practical experience. VCU emphasises undergraduate research, mentoring and experiential learning, and the department typically encourages students to present work, engage in summer research and take advantage of study‑away or exchange arrangements to broaden their academic experience.