Ohio University

What you'll study

The programme builds a core of pure and applied mathematics alongside courses in scientific computing and computer programming. Early coursework typically covers calculus, multivariable calculus, linear algebra and differential equations to establish analytical tools. More specialised computational topics include numerical analysis, computational linear algebra, numerical solutions of ordinary and partial differential equations, scientific programming (often using languages such as Python, MATLAB or C), and algorithms.

Students also study probability and mathematical statistics, mathematical modelling and optimisation, and are encouraged to take elective modules from computer science, engineering or data science to broaden practical skills. The degree often culminates in a senior seminar, capstone project or undergraduate research experience that emphasises computational modelling, data analysis or algorithm development.

• Core analysis: real analysis or foundations of advanced calculus
• Applied courses: numerical methods, scientific computing, mathematical modelling
• Computing: programming, data structures, algorithms, software for numerical computation
• Supporting modules: probability & statistics, linear algebra, differential equations, optimisation
• Capstone or research project integrating mathematics and computation

Entry requirements

Applicants are expected to have a high-school diploma or equivalent with strong performance in mathematics. Background in calculus or pre-calculus is recommended; coursework or experience in computer science is advantageous but not strictly required. Admissions consider overall academic record, recommendations and personal statements that demonstrate quantitative aptitude and motivation for the subject.

International applicants should present equivalent secondary credentials and evidence of English language proficiency where required. Students transferring from other institutions typically must submit transcripts and may need to meet departmental placement requirements to determine appropriate course level.

Career prospects

Graduates with a computational mathematics emphasis are well placed for roles that require strong quantitative and programming skills. Common career paths include data analyst or data scientist, software developer, quantitative or risk analyst in finance, operations researcher, simulation and modelling specialist, and roles in engineering and scientific computing. Many graduates also progress to postgraduate study in applied mathematics, computer science, statistics, engineering or related disciplines.

Employers include technology companies, financial institutions, government agencies, research labs and engineering firms. The degree develops transferable skills—problem-solving, numerical reasoning, algorithmic thinking and software competency—that are valued across industry sectors.

Why study at Ohio University

Ohio University’s Department of Mathematics provides a combination of strong mathematical training and opportunities for hands-on computational work. Undergraduates can take advantage of faculty-led research projects, interdisciplinary collaboration with computer science and engineering, and experiential learning through capstone projects and internships.

The department emphasises small classes and faculty accessibility, allowing students personalised mentoring and early involvement in research. University computing resources and lab facilities support numerical experimentation and large-scale computation, while the Athens campus offers a supportive environment for study and collaboration. These features make Ohio University a good choice for students seeking a rigorous mathematics degree with practical computational and programming skills.