Idaho State University

What you'll study

The Computational Mathematics master’s programme emphasises the design, analysis and implementation of numerical methods to solve problems arising in science, engineering and data-driven fields. Core topics typically include numerical analysis, numerical linear algebra, computational partial differential equations, and optimisation methods.

• Fundamental coursework in advanced calculus, real analysis and applied linear algebra to provide theoretical grounding.
• Numerical analysis covering accuracy, stability and convergence of algorithms.
• Computational methods for ordinary and partial differential equations, including finite element and spectral methods.
• Numerical linear algebra and iterative solvers for large-scale systems.
• Scientific computing topics such as high-performance computing, parallel algorithms and software development for numerical applications.
• Electives in optimisation, stochastic modelling, computational statistics or machine learning to support interdisciplinary applications.
• A research project or thesis option that involves implementing and testing algorithms on realistic problems, often including collaboration with faculty in applied mathematics, engineering or the physical sciences.

The programme is offered with flexible pathways, commonly including a thesis track for students aiming at research or PhD study and a non-thesis coursework/project track for those targeting industry roles. Students gain hands-on experience with mathematical software and programming languages commonly used in computational work.

Entry requirements

• A bachelor’s degree in mathematics or a closely related discipline (applied mathematics, physics, engineering, computer science) from an accredited institution.
• Solid preparation in calculus, linear algebra and differential equations; prior coursework in numerical analysis or scientific computing is strongly recommended.
• A competitive undergraduate GPA; programmes typically expect evidence of strong quantitative performance.
• Proficiency in programming (for example Python, MATLAB, C/C++ or Fortran) is expected; applicants without formal programming coursework should demonstrate equivalent experience.
• Application materials usually include official transcripts, a statement of purpose outlining research or career goals, and one or more letters of recommendation. A curriculum vitae or résumé is also standard.
• International applicants must meet the university’s English language proficiency requirements; additional documentation or evaluations may be required for students from outside the domestic system.

Career prospects

Graduates with a master’s in Computational Mathematics are prepared for a wide range of roles that demand strong mathematical modelling and computational skills. Common career paths include:

• Computational scientist or numerical analyst in research laboratories and engineering firms.
• Data scientist, quantitative analyst or model developer in finance, insurance and tech companies.
• Software developer focusing on scientific and numerical computing libraries or simulation packages.
• Roles in energy, environmental modelling, aerospace and manufacturing that require simulation and optimisation expertise.
• Positions at national laboratories or government research centres where large-scale simulation and high-performance computing are central.
• Further academic study — many graduates use the MS as preparation for PhD programmes in applied mathematics, computational science or related disciplines.

Why study at Idaho State University

Idaho State University offers a computational mathematics programme that integrates theoretical training with applied, hands-on computing. Students benefit from relatively small class sizes and close mentoring by faculty whose research spans numerical analysis, modelling, optimisation and interdisciplinary collaborations.

• Opportunities to work on applied research projects with faculty and collaborators in engineering, physics and the health sciences.
• Access to campus computing resources and training in the use of scientific software and parallel computing environments.
• Potential for graduate assistantships and research positions that provide teaching experience and financial support while developing practical skills.
• Proximity and institutional connections to regional research organisations and national laboratories, offering internship and employment pathways for computational specialists.

Overall, the programme is well suited to students who want a balance of mathematical rigour and practical computational training that prepares them for research roles or technical careers in industry and government.