University of Chicago

What you'll study

The Computational Mathematics pathway blends core courses in analysis, algebra and discrete mathematics with applied and computational subjects. You will develop mathematical rigour—real analysis, abstract algebra and topology—while also studying numerical analysis, scientific computing, numerical linear algebra, partial differential equations and optimisation methods. Core computational topics include algorithms and data structures, numerical methods for differential equations, high-performance computing, probabilistic modelling and computational statistics.

Typical course components include a sequence in calculus and linear algebra, introductory real analysis, courses in applied mathematics (numerical analysis, approximation theory), computational probability and statistics, and programming-focused modules taught in languages commonly used in scientific computing (e.g. Python, C/C++ or Julia). Electives let you apply tools to domains such as machine learning, computational biology, computational finance and cryptography. The programme emphasises project work: coursework commonly culminates in a senior thesis or capstone project involving original computation or modelling, and there are frequent opportunities for faculty-supervised undergraduate research.

Students may cross-register or take electives in Computer Science, Statistics, Physics, Economics and the interdisciplinary Computation Institute. The department encourages developing strong software engineering practice, reproducible research workflows and experience with parallel and GPU computing for large-scale problems.

Entry requirements

Applicants should demonstrate a strong background in secondary-school mathematics, including calculus and an introduction to proof-based work where available. Successful candidates typically show evidence of advanced quantitative coursework (for example advanced calculus/AP or IB Higher Level mathematics), strong performance in mathematics and related sciences, and programming experience or coursework in computer science.

Admissions to the University of Chicago are holistic. Academic preparation is important, but the department looks for intellectual curiosity, problem-solving ability and mathematical maturity. International applicants should present the equivalent secondary credentials from their country; applicants whose first language is not English will need to meet the university's English proficiency requirements through recognised tests or equivalent evidence.

Career prospects

Graduates with a computational mathematics background enter a range of quantitative and technical roles. Common career paths include:

• Data scientist, machine learning engineer or quantitative analyst in finance and fintech
• Software engineer working on numerical libraries, simulation engines or scientific applications
• Applied mathematician or computational modeller in industry and government labs (energy, aerospace, climate, bioinformatics)
• Research scientist and PhD candidate in mathematics, applied mathematics, statistics, computer science or computational science
• Actuarial roles and analytics positions in consulting and insurance

Graduates are well prepared for roles requiring both theoretical insight and practical coding ability, and many move on to competitive graduate programmes or research positions at national laboratories, research institutes and technology companies.

Why study at University of Chicago

The University of Chicago offers a rigorous mathematical education emphasising both depth and breadth. The Mathematics Department is well known for its strong faculty in pure and applied mathematics and for interdisciplinary collaboration with Computer Science, Statistics and the Computation Institute. Students benefit from close faculty mentorship, opportunities for undergraduate research, and access to advanced computing resources.

The university’s connections with local financial institutions, research centres and national laboratories—alongside the joint Computation Institute partnership with Argonne National Laboratory—provide practical pathways for internships and collaborative projects. The college’s culture of intellectual inquiry, combined with structured core mathematics training and hands-on computational experience, prepares graduates for technically demanding careers and competitive postgraduate study.