Eastern Michigan University

What you'll study

The Computational Mathematics pathway builds a strong foundation in pure and applied mathematics while emphasising numerical methods, scientific computing and algorithmic problem solving. The programme blends core mathematics courses with computing and applied electives so you learn both the theory and the tools used to implement mathematical models.

• Core mathematics: single-variable and multivariable calculus, linear algebra, ordinary differential equations, real analysis or foundations of advanced calculus.
• Computational core: numerical analysis, numerical linear algebra, scientific computing, numerical solutions of differential equations and numerical optimisation.
• Programming and tools: courses that develop practical programming skills (commonly using languages and environments such as Python, MATLAB or comparable tools), data structures and algorithms relevant to numerical work.
• Probability and statistics: introductory and applied probability, mathematical statistics and computational statistics for modelling and inference.
• Modelling and applications: mathematical modelling, computational methods in applied disciplines (for example physics, engineering, finance or biology) and project-based coursework that links mathematics to real problems.
• Capstone / research: a senior seminar, capstone project or undergraduate research opportunity that typically requires implementing and analysing a computational model or numerical method.
• Electives: options to take electives in computer science, data science, operations research, applied physics or economics to tailor the degree toward industry or further study.

Entry requirements

Admission to the undergraduate mathematics programme is through Eastern Michigan University's standard undergraduate admissions process. Applicants will be expected to demonstrate a strong high-school mathematics background and readiness for university-level calculus.

• High-school diploma or equivalent with a record that shows strength in mathematics courses (pre-calculus and calculus are recommended).
• Official high-school transcripts; transfer applicants should provide college transcripts showing coursework and grades.
• Standardised test scores (SAT/ACT) may be considered where required by the university; applicants should check the university admissions page for current testing policies.
• International applicants must satisfy the university's English proficiency requirements (for example via TOEFL or IELTS) and submit credential evaluations as requested.
• Some students may be placed into appropriate first-year mathematics courses based on placement testing or prior coursework.

Career prospects

Graduates with a computational mathematics specialisation are well prepared for a variety of roles that require mathematical modelling, numerical computation and programming. The degree serves as strong preparation for immediate employment or for graduate study in mathematics, computer science, engineering or data science.

• Data scientist / data analyst — using statistical and computational tools to extract insight from data.
• Software or algorithm engineer — developing and optimising numerical algorithms and scientific software.
• Quantitative analyst / financial modeller — applying numerical methods in finance and risk management.
• Operations research / optimisation specialist — formulating and solving optimisation problems for logistics, manufacturing and services.
• Actuarial analyst — provided additional credentialing and coursework in probability and finance.
• Research and graduate study — master's or doctoral research in applied mathematics, computational science or related fields.
• Government, national laboratories and industry roles that require modelling, simulation and data-driven decision making.

Why study at Eastern Michigan University

Eastern Michigan University's Department of Mathematics and Statistics offers a student-centred undergraduate experience with direct access to faculty and opportunities for hands-on computational work. The programme emphasises practical skills alongside mathematical rigour, preparing students to apply techniques to real problems.

• Faculty mentorship: small class sizes and accessible faculty facilitate mentoring, undergraduate research and project supervision.
• Computing resources: access to departmental computing facilities and software commonly used in numerical and data analysis work.
• Interdisciplinary connections: ease of collaboration with computer science, engineering, physics and business programmes to tailor study toward internships and applied careers.
• Location and industry links: proximity to the Detroit–Ann Arbor region provides internship and employment opportunities with regional companies, research labs and public-sector organisations.
• Career support: university career services, advising and departmental guidance help students prepare for job searches, internships and graduate applications.