University of Michigan

What you'll study

This programme grounds you in core undergraduate mathematics—calculus, linear algebra, real analysis and differential equations—while emphasising numerical methods, scientific computing and algorithmic implementation. Typical topics and modules include:

• Foundations: multivariable calculus, linear algebra, proof-based courses in real analysis and abstract algebra.
• Computation and algorithms: numerical analysis, numerical linear algebra, algorithms and data structures, and computational complexity.
• Modelling and applications: ordinary and partial differential equations, mathematical modelling, simulation, and computational methods for PDEs.
• Statistics and probability: probability theory, mathematical statistics and data-analysis methods relevant for computational work.
• Practical programming and software: coursework and labs using high-level and scientific languages (such as Python, MATLAB, or C/C++), version control, and high-performance or parallel computing techniques.
• Electives and depth: advanced electives in optimisation, machine learning, computational geometry, scientific visualization, and domain-specific applications drawn from physics, engineering, finance or biology.
• Capstone or research: options frequently include a senior project, honours thesis or participation in faculty-led undergraduate research, allowing you to apply computational methods to an open problem.

The curriculum is designed to be flexible so students can pair computational mathematics with complementary minors or majors (for example computer science, statistics, engineering or a science discipline) and to prepare for graduate study or direct entry into technical careers.

Entry requirements

Admission to the University of Michigan is competitive and typically requires a strong secondary-school academic record with significant preparation in mathematics. Successful applicants usually present:

• Advanced coursework in mathematics (calculus and, where available, higher-level maths such as multivariable calculus or IB Higher Level mathematics).
• Complementary coursework in science and computing, and strong overall academic performance across a demanding high-school curriculum.
• Evidence of quantitative and problem-solving ability shown through coursework, standardised test scores if submitted, teacher recommendations and extracurricular activities such as math competitions, programming projects or research.

Transfer applicants should demonstrate completion of equivalent university-level calculus and introductory linear algebra courses. International applicants must meet the University’s general admissions and English language proficiency requirements. The Mathematics department may have additional preparation expectations for specific tracks; consult departmental admissions guidance when preparing your application.

Career prospects

Graduates with a computational mathematics background are sought after in a wide range of roles where quantitative modelling and algorithmic thinking are essential. Common career paths include:

• Data science and analytics — building statistical models, feature engineering and applied machine learning.
• Software engineering and systems development — implementing efficient numerical algorithms and scientific software.
• Quantitative finance and risk modelling — modelling markets, derivatives pricing and portfolio optimisation.
• Computational science and engineering — simulation, high-performance computing and interdisciplinary research in physics, engineering and biology.
• Operations research and optimisation — supply chain modelling, logistics, and decision-support systems.
• Graduate study and research — masters or PhD programmes in applied mathematics, computational science, statistics, computer science or engineering.

Students benefit from the University of Michigan’s career services, industry connections in the Midwest and beyond, internship opportunities, and a strong alumni network that help transition into roles in industry, government laboratories and academia.

Why study at University of Michigan

The University of Michigan offers a strong mathematical curriculum combined with rich computational resources and interdisciplinary collaboration. The Mathematics Department is supported by active research centres and institutes—such as those focused on computational discovery and engineering—which create opportunities for undergraduate research and team projects.

Other advantages include access to high-performance computing infrastructure, a broad choice of elective courses across computer science, statistics and engineering, and numerous student organisations and seminars that deepen practical and professional skills. The Ann Arbor campus and the university’s industry relationships provide a lively environment for internships, entrepreneurship and applied research, making it a strong setting for students who want both theoretical depth and hands-on computational experience.