Montana State University

What you'll study

This programme blends core mathematics courses with a strong focus on numerical methods, scientific computing and algorithmic problem solving. Students develop mathematical maturity while gaining practical experience in programming and the use of computational tools.

• Core mathematical foundations: sequences of calculus (single and multivariable), linear algebra, real analysis and differential equations to build rigorous analytical skills.
• Computational mathematics and numerical analysis: courses in numerical linear algebra, numerical solution of ordinary and partial differential equations, numerical optimisation and error analysis.
• Computer science and programming: instruction in programming languages commonly used in scientific computing (for example Python, C/C++ or MATLAB), data structures, and basic algorithms to support numerical work.
• Probability and statistics: probability theory, mathematical statistics and computational statistics to support modelling and data analysis tasks.
• Modelling and applications: mathematical modelling courses emphasising applications in physical sciences, engineering, finance, and biology, often using computational experiments and simulation.
• Electives and special topics: options may include optimisation, computational geometry, scientific visualisation, machine learning, high-performance computing and advanced topics in applied analysis.
• Capstone and research experiences: a senior project, computational capstone or faculty-mentored undergraduate research project that integrates theory, numerical methods and software implementation.

The degree typically follows a structured four-year curriculum combining mathematics major requirements, supporting coursework in computer science and statistics, and general education classes. Students are encouraged to take practicum-style experiences such as internships, collaborative research and industry projects.

Entry requirements

Admission to the Bachelor of Science in Mathematics (Computational Mathematics emphasis) normally requires a high school diploma or equivalent with a strong record in mathematics. Typical preparation includes completion of algebra, geometry, trigonometry and calculus where available.

• Academic preparation: strong performance in high school mathematics; familiarity with calculus is highly recommended.
• Supporting subjects: coursework in physics, computer science or statistics is advantageous but not always mandatory.
• Standardised tests and transcripts: Montana State University follows its published undergraduate admissions policies regarding test scores and transcripts; applicants should consult the university for current guidance on standardised tests.
• International applicants: must demonstrate equivalent academic credentials and English language proficiency through recognised tests or approved alternatives under the university’s international admissions requirements.
• Placement and advising: incoming students may take mathematics placement assessments to ensure they begin at an appropriate level; early advising helps plan a pathway through core and computational coursework.

Career prospects

Graduates with a computational mathematics specialisation are equipped for a wide range of technical careers that require mathematical modelling, numerical simulation and programming skills.

• Industry roles: positions such as data analyst, quantitative analyst, modelling engineer, simulation scientist or software developer in technology, engineering, energy and finance sectors.
• Research and science: roles supporting scientific research with computational tools in fields such as physical sciences, environmental science, bioinformatics and engineering.
• Government and national labs: numerical modelling and computational analysis positions in government agencies and laboratories where simulation and data-driven decision making are needed.
• Further study: many graduates pursue graduate programmes in applied mathematics, computational science, data science, statistics, computer science or engineering.
• Entrepreneurship and consulting: opportunities to work in technical consulting or to apply computational skills in startup environments and product development.

Why study at Montana State University

Montana State University offers a mathematics curriculum with direct connections to computational research and interdisciplinary applications. The Department of Mathematical Sciences provides personalised faculty mentorship, opportunities for undergraduate research, and collaboration with neighbouring departments such as computer science, statistics and engineering.

• Research opportunities: students can engage in faculty-led projects and applied research that draw on local natural-resource challenges and broader scientific problems, gaining hands-on computational experience.
• Computing resources: access to departmental computing labs and campus high-performance computing resources supports coursework and large-scale numerical projects.
• Experiential learning: a range of internships, industry partnerships and capstone projects help students transition from academic study to professional roles.
• Supportive learning environment: the university emphasises small-class interaction within the major, advising for career and graduate-school planning, and extracurricular opportunities such as student organisations and seminar series.

Together these elements prepare graduates to apply mathematical and computational thinking to real problems and to pursue diverse career paths or advanced study.