Pittsburg State University

What you'll study

The programme combines rigorous mathematical theory with practical computational techniques. Core areas typically covered include numerical analysis, numerical linear algebra, scientific computing, and numerical solution of ordinary and partial differential equations. You will also study topics such as optimisation methods, computational probability and stochastic modelling, finite element and finite difference methods, and mathematical modelling of physical systems.

Training in scientific programming and software engineering is an integral part of the programme; students gain hands-on experience with languages and tools commonly used in computational mathematics (for example Python, MATLAB, C/C++ and parallel computing libraries). Coursework emphasises algorithm design, error analysis, stability and performance, and reproducible computational research.

The degree is offered with options that allow a research thesis or a project-based capstone. Typical study includes a mix of advanced coursework, a supervised research project or thesis, and opportunities for teaching or research assistantships. Elective modules support interdisciplinary work with departments such as Computer Science, Engineering or Applied Sciences.

Entry requirements

Applicants are expected to hold a good honours degree in mathematics or a closely related discipline (for example applied mathematics, statistics, physics, engineering or computer science) with substantial quantitative content. Candidates should demonstrate competence in calculus, linear algebra and differential equations, and be familiar with basic programming concepts.

Where applicants’ first language is not English, evidence of proficiency in English is required. Applicants with relevant professional experience, post-baccalaureate coursework, or strong performance in undergraduate research may also be considered. Admission may be conditional on completion of specific undergraduate prerequisites where gaps are identified.

Career prospects

Graduates leave equipped to work in roles that require advanced computational and mathematical skills. Typical career destinations include research scientist or computational modeller in industry and government laboratories, quantitative analyst in finance or insurance, data scientist or machine learning practitioner, scientific software developer, and roles in engineering simulation and optimisation.

Other career paths include continuing to doctoral study in applied mathematics, computational science or related fields, teaching and academic posts, and technical positions in sectors that rely on modelling and simulation such as aerospace, energy, bioinformatics and environmental modelling.

Why study at Pittsburg State University

Pittsburg State University offers a supportive graduate environment with relatively small class sizes and close access to faculty mentors. The mathematics department emphasises applied and computational research, with opportunities to work alongside researchers in engineering, computer science and the physical sciences.

Students benefit from hands-on access to computing facilities and the chance to gain practical experience through research assistantships and collaborative projects. The university’s focus on applied training makes this programme appropriate for students seeking industry-relevant skills as well as those preparing for further research or doctoral study.