University of Iowa

What you'll study

The programme emphasises the development of mathematical modelling, analytical techniques and computational skills used to study problems arising in science, engineering and technology. Students follow a programme of advanced coursework combined with a substantial project or thesis under faculty supervision.

• Core topics commonly include ordinary and partial differential equations, numerical analysis and scientific computing, dynamical systems and stability theory, and optimisation methods.
• Applied and elective modules often cover mathematical modelling in fluids, materials or biology, stochastic processes and applied probability, inverse problems and data assimilation, high‑performance computation, and statistical learning for applied problems.
• Students typically complete a combination of lecture courses and seminars, a computational or theoretical project, and either a written thesis or a final project/report. Coursework load and the balance between research and classes may be tailored to suit thesis and non‑thesis options.
• Seminar series, departmental colloquia and opportunities to collaborate with neighbouring departments—such as engineering, physics, statistics and biology—support interdisciplinary training.

Entry requirements

Applicants should hold a bachelor’s degree in mathematics, applied mathematics, physics, engineering, computer science or a closely related quantitative field. A solid foundation in calculus, linear algebra, differential equations, and basic real analysis is expected.

• Academic transcripts demonstrating strong quantitative performance are required.
• Typical supporting materials include a statement of purpose, two or three letters of recommendation, and a CV or résumé.
• GRE scores may be submitted where available, though requirements can vary; consult the department for guidance.
• International applicants must demonstrate proficiency in English through recognised tests unless exempt; specific test score requirements are set by the university.
• Candidates with non‑standard backgrounds may be admitted conditionally and asked to complete prerequisite coursework.

Career prospects

Graduates with an MS in Applied Mathematics are prepared for a wide range of roles in industry, government and academia. The training in modelling, computation and quantitative reasoning is applicable across sectors that rely on data analysis and mathematical methods.

• Common career paths include data scientist, quantitative analyst, modelling scientist, operations researcher, and computational scientist in industries such as finance, technology, energy, manufacturing and biotech.
• Graduates often take positions in government laboratories, research institutes and consulting firms where mathematical modelling and simulation are central.
• The programme also prepares students for doctoral study in applied mathematics, computational science, statistics or related disciplines.

Why study at University of Iowa

The University of Iowa’s Department of Mathematics offers a collaborative environment with active research groups in applied analysis, computational mathematics and interdisciplinary areas. Students benefit from close mentorship by faculty engaged in both theoretical and computational research and from collaboration opportunities with engineering, physics, statistics and life‑science researchers.

• Access to departmental seminars, research‑oriented coursework and computing facilities supports practical skill development.
• Teaching assistantships and research assistantships are available to graduate students, providing financial support and teaching experience.
• Iowa City’s academic community and its connections with regional and national research networks create opportunities for internships, joint projects and career networking.