University of Cincinnati

What you'll study

This programme emphasises mathematical modelling, numerical analysis and algorithmic implementation. Core topics typically include numerical linear algebra, numerical solution of ordinary and partial differential equations, scientific computing and error analysis. Students also study complementary subjects such as optimisation, probability and statistics, computational techniques for data analysis, and elements of high‑performance and parallel computing.

The degree is offered with flexible study pathways: a coursework route with a substantial applied project and a research (thesis) route for students intending to continue to doctoral study. Typical taught modules include:

• Numerical Analysis and Approximation Theory
• Numerical Linear Algebra and Matrix Computations
• Scientific Computing and Software for Numerical Simulation
• Numerical Methods for Partial Differential Equations
• Optimisation and Computational Methods
• Computational Probability, Statistics and Data Analysis
• High‑Performance and Parallel Computing (tools and practices)
• Modelling and Simulation in Applied Sciences and Engineering

Students typically gain hands‑on experience developing and testing algorithms in programming languages commonly used in scientific computing (for example Python, MATLAB, C/C++ or Fortran) and learn to use numerical libraries and parallel frameworks. Opportunities exist to take elective courses from related departments such as Computer Science, Engineering or Finance to tailor the programme to applied interests.

Entry requirements

Applicants should hold a bachelor’s degree in mathematics, applied mathematics, statistics, engineering, physics, computer science or a closely related discipline, with a strong background in undergraduate calculus, linear algebra and differential equations. Prior exposure to numerical methods, scientific computing or programming is strongly recommended.

Typical application materials include official transcripts, a statement of purpose outlining academic and career goals, letters of recommendation, and a CV. International applicants must demonstrate English language proficiency by submitting an approved test score unless exempt by institutional policy. Some applicants may be asked to provide examples of prior coursework or project work in computational mathematics; an interview or additional assessment may be used in a small number of cases.

Career prospects

Graduates are prepared for roles that combine mathematical rigour with computational skill. Common career destinations include data scientist or analyst roles, quantitative analyst positions in finance, software engineer or developer jobs with a focus on scientific computing, and computational scientist roles in industry or national research laboratories. The programme also provides a solid foundation for those continuing to PhD programmes in applied mathematics, computational science or related fields.

Students frequently find roles in sectors such as engineering, finance, energy, pharmaceuticals, defence and technology, or join multidisciplinary teams in research institutes and government agencies where modelling, simulation and large‑scale computation are essential.

Why study at University of Cincinnati

The University of Cincinnati combines strong mathematical teaching with practical, application‑oriented training. The department fosters close faculty‑student interaction and offers opportunities to engage in applied research projects that draw on collaborations with engineering, computer science and other research units across campus.

A distinctive advantage for students is access to experiential learning pathways and industry connections that help bridge academic study and professional practice. Computational mathematics students benefit from computing facilities and software resources available on campus, and from chances to work on real problems through research projects, internships or industry partnerships. The programme’s flexibility of coursework and thesis/project options makes it suitable for both career‑oriented students and those preparing for doctoral study.