Indiana University

What you'll study

This programme builds a strong foundation in pure and applied mathematics while emphasising numerical methods, scientific computing and algorithmic thinking. Core subjects typically include multivariable calculus, linear algebra, ordinary differential equations and real analysis, paired with computational courses such as numerical analysis, scientific computing, numerical linear algebra and methods for partial differential equations.

• Introductory and advanced calculus sequence
• Linear algebra and matrix theory
• Real analysis and proof-based mathematics
• Ordinary and partial differential equations
• Numerical analysis and numerical linear algebra
• Scientific computing, algorithm design and complexity
• Probability, statistics and stochastic modelling
• Programming for mathematicians (Python, MATLAB, or similar)
• Computational project or capstone involving modelling, simulation or data analysis
• Electives from applied mathematics, computer science, data science, engineering or physics

Students often complement mathematics coursework with classes in the Luddy School of Informatics, Computing, and Engineering or with electives in statistics and data science to deepen programming, machine learning and data-handling expertise. Opportunities for undergraduate research, team-based projects and internships are integrated into the programme.

Entry requirements

Applicants are expected to hold a high school diploma or equivalent with a strong background in mathematics. Recommended preparation includes one or more years of calculus, algebra and coursework that demonstrates quantitative reasoning skills. Admissions to Indiana University consider academic records, extracurricular activities and personal statements; standardised test policies may vary, so applicants should consult the university for current guidance.

International applicants must meet English language proficiency requirements through an accepted test or approved pathway and provide academic credentials equivalent to the US secondary-school completion. Students transferring from other institutions should present university transcripts and have completed introductory calculus and other foundational mathematics to be considered for advanced placement.

Career prospects

Graduates with a computational mathematics degree are prepared for roles that require mathematical modelling, numerical simulation and data-driven problem solving. Common career paths include:

• Data scientist or analyst, applying statistical and computational techniques to extract insights from data
• Quantitative analyst in finance, risk modelling and algorithmic trading
• Software developer or engineer focusing on scientific computing, numerical libraries or high-performance computing
• Actuarial analyst, using probability and statistics for insurance and pension modelling
• Research roles in national labs, industry R&D or university research groups
• Graduate study in applied mathematics, computer science, data science, engineering or related fields

Employers range from technology and finance companies to government research labs, engineering firms and academic institutions. The programme’s combination of rigorous mathematics and practical computing skills is valued across sectors that require trustworthy quantitative analysis and scalable computational solutions.

Why study at Indiana University

Indiana University offers a mathematics programme with access to strong research-active faculty and interdisciplinary collaborations across computing, statistics and the sciences. The campus provides computing resources and research infrastructure that support numerical and data-intensive projects, and students can engage with research groups or pursue internships facilitated by the university’s industry connections.

Studying at Indiana University gives students flexibility to tailor the degree through electives and minors, close mentoring from faculty, and opportunities to participate in undergraduate research and collaborative projects. For students who want to bridge theoretical mathematics and practical computation, the programme provides both the conceptual depth and the hands-on experience employers and graduate programmes seek.