University of Chicago

What you'll study

The programme emphasises core mathematical methods and their application to real-world problems. Typical topics include advanced calculus and real analysis, ordinary and partial differential equations, numerical analysis and scientific computing, probability and stochastic processes, optimisation and variational methods, and mathematical modelling. Students also take courses in applied linear algebra, spectral methods, and topics in computational mathematics.

Coursework combines theory with computational practice: students learn to formulate problems, prove relevant results, and implement numerical solutions using modern software. The degree commonly includes a mix of required core units, elective courses that permit specialisation (for example in fluid dynamics, mathematical biology, inverse problems, or financial mathematics), and seminar work. Many students choose either a supervised master’s thesis or a capstone project that partners with faculty or collaborators from other units across the University.

Entry requirements

Applicants are expected to hold a bachelor’s degree (or equivalent) with substantial preparation in mathematics. Typical preparation includes multivariable calculus, linear algebra, differential equations, and an introduction to proofs; background in real analysis and basic probability/statistics is highly desirable. Programming experience and exposure to numerical methods are advantageous for computational components of the programme.

Applications normally require a transcript, a personal statement explaining academic and career goals, and letters of recommendation. International applicants must demonstrate English proficiency according to University regulations. Some applicants may also submit a CV and representative work (for example, a project report or thesis). The department evaluates applicants on the strength of their mathematical preparation, quantitative aptitude, and fit with faculty research interests.

Career prospects

Graduates pursue careers across industry, government and academia. Common roles include quantitative analyst and model developer in finance, data scientist or machine learning engineer in technology and start-ups, research scientist in industrial R&D, computational scientist in engineering and energy sectors, and applied mathematician in national laboratories. Many graduates also continue to PhD programmes in applied mathematics, computational science, statistics, or related disciplines.

The programme’s combination of theoretical rigour and computational training is designed to make alumni competitive for roles that require both mathematical depth and practical implementation skills. Students also benefit from the University’s career services and connections across campus, which help with internships and employer engagement in the Chicago metropolitan area and beyond.

Why study at University of Chicago

The University of Chicago is known for its strong mathematical tradition and emphasis on rigorous, concept-driven teaching. Within the Department of Mathematics and related centres, students have access to faculty working at the forefront of analysis, numerical methods, probability and interdisciplinary applications. The University’s environment encourages cross-disciplinary collaboration with neighbouring units—such as computer science, physics, economics and the Booth School of Business—enabling applied projects that bridge theory and practice.

Students benefit from regular research seminars, colloquia and computing resources, as well as opportunities to collaborate with national laboratories and local industry partners. The programme’s location in Chicago provides access to a broad professional ecosystem for internships and employment, while the University’s alumni network supports career development worldwide.