Radford University

What you'll study

The Computational Mathematics concentration blends core mathematical foundations with numerical methods and scientific computing. The programme is organised across a standard undergraduate sequence, combining general education requirements, core mathematics courses, concentration electives and a culminating project or seminar.

• Core mathematics: calculus sequence, linear algebra, ordinary differential equations and real analysis to establish rigorous foundations.
• Computational and applied courses: numerical analysis, scientific computing, mathematical modelling, numerical linear algebra, and optimisation methods for continuous and discrete problems.
• Programming and tools: coursework and labs that emphasise programming in languages commonly used for computation (for example Python, MATLAB, or similar), version control, and high-performance computing concepts.
• Probability and statistics: probability theory, mathematical statistics and applied data analysis to support work in data-driven modelling and uncertainty quantification.
• Electives: options such as discrete mathematics, graph theory, computational geometry, machine learning, cryptography or differential equations models allow students to tailor the degree to interests.
• Capstone experience: a senior project or practicum in which students apply computational mathematics to a substantive problem, often working closely with a faculty mentor or in collaboration with external partners.

Entry requirements

Applicants should hold a high school diploma or recognised equivalent with a strong foundation in mathematics, typically including algebra, geometry and pre-calculus or calculus. Admissions consider the overall academic record and readiness for college-level mathematics.

• High school transcripts demonstrating sustained performance in mathematics.
• Information about college preparatory coursework; applicants who have completed college-level calculus or AP/IB mathematics may place into advanced courses.
• Some programmes request a personal statement or academic interest statement, and one or more letters of recommendation can strengthen an application.
• Standardised test scores (SAT/ACT) policies may vary; consult the university for current guidance. Transfer applicants should provide college transcripts and descriptions of completed math courses for placement evaluation.
• International applicants must demonstrate equivalent secondary credentials and English language proficiency according to the university’s published requirements.

Career prospects

Graduates with a computational mathematics background move into a wide range of technical and analytical roles. The programme prepares students for positions that require mathematical modelling, numerical simulation and data analysis.

• Data analyst or data scientist roles in business, healthcare, or government.
• Quantitative analyst or modelling positions in finance and insurance, including preparation for actuarial examinations if desired.
• Software development and engineering roles that require strong numerical and algorithmic skills.
• Research and technical roles in engineering, physical sciences or environmental modelling, including opportunities in high-performance computing.
• Further study at graduate level in applied mathematics, computational science, statistics, computer science or related fields.

Why study at Radford University

Radford University offers a personalised undergraduate experience with relatively small class sizes and direct access to faculty, which benefits students pursuing computational mathematics. The department emphasises undergraduate research and hands-on learning through projects and practicum experiences.

• Faculty mentorship: accessible faculty who supervise capstone projects and undergraduate research in applied and computational topics.
• Computing resources: access to departmental labs and software used for numerical simulation, data analysis and scientific computing.
• Interdisciplinary opportunities: collaborations across departments — such as computer science, physics, engineering and business — allow students to apply computational methods to varied domains.
• Career support: advising, internship facilitation and connections with regional employers help translate classroom learning into practical experience.