University of Alabama

What you'll study

The Computational Mathematics pathway builds on the core undergraduate mathematics curriculum while emphasising numerical methods, scientific computing and algorithmic thinking. The programme is typically structured over four years and mixes core theory courses, computational laboratories and applied electives.

• Core mathematics: single- and multivariable calculus, linear algebra, differential equations and discrete mathematics provide the foundational theory.
• Analysis and theory: courses in real analysis and complex analysis or an introduction to proofs to develop mathematical rigour and abstraction.
• Computational and applied courses: numerical analysis, scientific computing, numerical linear algebra, computational differential equations and numerical optimisation, emphasising both theory and implementation.
• Programming and software: practical training in programming languages and tools commonly used in computational mathematics (for example Python, MATLAB, C/C++ or Julia), version control, and high-performance computing concepts.
• Probability and statistics: probability theory, mathematical statistics and data analysis to support modelling and uncertainty quantification.
• Electives and interdisciplinary options: applied elective choices such as computational physics, mathematical finance, machine learning, cryptography, scientific visualisation or computational biology, allowing tailoring to career interests.
• Capstone / senior project: a supervised project or practicum that typically requires students to formulate a computational problem, implement numerical solutions and present results—often undertaken in collaboration with faculty or external partners.

Entry requirements

Applicants are expected to have a strong background in high-school mathematics. For domestic applicants this usually means completion of a rigorous maths sequence (calculus is strongly recommended) and solid grades across STEM subjects. International applicants should present equivalent qualifications with evidence of strong performance in mathematics.

• Successful applicants typically demonstrate proficiency in calculus and algebra; taking further mathematics courses (where available) is advantageous.
• Incoming students may need to take placement tests to determine the appropriate starting mathematics course.
• Transfer applicants should have completed college-level calculus and associated coursework with good standing and will be evaluated for transfer credit on an individual basis.
• Personal statements, references and relevant extracurricular experience (math competitions, research projects, programming experience or internships) can strengthen an application.

Career prospects

Graduates with a computational mathematics degree are well placed for roles that require quantitative modelling, numerical simulation and software skills. Employers value the combination of mathematical reasoning and practical computational ability.

• Typical career paths include data scientist/analyst, quantitative analyst in finance, software developer for scientific applications, computational modeller for engineering or physical sciences, and roles in operations research and optimisation.
• Graduates also move into specialised technical roles in industries such as aerospace, energy, biotech, finance, and defence, or into government laboratories and research institutes.
• Many students continue to postgraduate study: master's programmes in applied mathematics, computational science, statistics, data science or PhD research in mathematical and computational disciplines.

Why study at University of Alabama

The University of Alabama offers a mathematics department with a balanced emphasis on teaching and research and provides undergraduates with opportunities for hands-on computational experience. Students benefit from small-class interactions with faculty, access to computing facilities and research groups, and a curriculum designed to connect mathematical theory with practical implementation.

• Undergraduate research and capstone projects supervised by active faculty provide direct experience in tackling real computational problems.
• Opportunities for internships and cooperative work placements leverage university connections with regional industry and national laboratories.
• Student-led clubs, math competitions and seminars help build professional skills, while advising and career services support preparation for employment or further study.