University of Tulsa

What you'll study

The programme emphasises rigorous mathematical foundations together with practical computational techniques. Students study advanced topics in ordinary and partial differential equations, numerical analysis, scientific computing and applied probability and statistics. Coursework typically covers subjects such as mathematical modelling, dynamical systems, numerical linear algebra, finite element and finite difference methods, optimisation, stochastic processes and data analysis.

Students can choose from a thesis route, which includes supervised research and a written thesis, or a coursework/project route that culminates in a substantial applied project. Seminar participation and a reading course or directed study with a faculty member are common components, giving exposure to current research problems in areas such as computational fluid dynamics, inverse problems, imaging, and mathematical biology.

Entry requirements

Applicants are normally expected to hold a bachelor’s degree in mathematics, applied mathematics, engineering, physics, computer science or a closely related field. Preparatory background usually includes multivariable calculus, ordinary differential equations, linear algebra, and introductory real analysis. Some programming experience (for example in Python, MATLAB or C) and exposure to numerical methods are strongly recommended.

Typical application materials include university transcripts, academic references, a personal statement outlining research or career goals, and a CV. International applicants must demonstrate English language proficiency according to the university’s general requirements. In some cases applicants without the standard background may be admitted conditionally and asked to take bridging coursework.

Career prospects

Graduates leave prepared for roles that require strong quantitative and computational skills. Common career destinations include data science and analytics, software and algorithm development, numerical modelling in engineering firms, finance and quantitative risk analysis, and technical roles in energy and environmental companies. Government laboratories and research institutes also recruit applied mathematicians for modelling and simulation work.

The degree also provides a solid foundation for further academic study; many students progress to PhD programmes in applied mathematics, computational science or related interdisciplinary fields. Hands-on project work and opportunities for collaboration with engineering and computer science departments help graduates build industry-relevant portfolios.

Why study at University of Tulsa

The University of Tulsa offers a small, focused mathematical sciences department where students work closely with faculty on research and applied projects. The department’s strengths include computational mathematics, numerical analysis and interdisciplinary collaboration with engineering, petroleum engineering and computer science, giving access to practical problems and industry contacts.

Graduate students benefit from dedicated computing resources, seminar series and opportunities for teaching or research assistantships. The university’s location provides proximity to a regional cluster of energy, aerospace and technology companies, which can support internships and employment opportunities for applied mathematicians.