University of Kansas

What you'll study

This programme combines core mathematics with computational and numerical methods. Early years focus on foundational courses such as calculus (single and multivariable), linear algebra, discrete mathematics and introductory proof-based mathematics. From there you move into more specialised and computational topics including numerical analysis, scientific computing, computational linear algebra, differential equations and partial differential equations, and approximation theory.

Students also take courses in probability and mathematical statistics, optimisation, and applied modelling. Programming and software skills are emphasised, typically through courses or modules that teach Python, MATLAB, or C/C++ for numerical work, as well as classes in algorithm design and data structures often offered in collaboration with the Department of Computer Science.

The degree usually culminates in a capstone experience such as a senior project, computational research project or honours thesis where students apply mathematical modelling and numerical methods to a real problem, often in collaboration with faculty from mathematics, engineering, computer science or the natural sciences.

• Foundations: Calculus sequence, Linear Algebra, Introductory Proofs
• Core Theory: Real Analysis, Ordinary Differential Equations
• Computational Mathematics: Numerical Analysis, Scientific Computing, Computational Linear Algebra
• Applied & Statistical Topics: Probability & Statistics, Mathematical Modelling, Optimisation
• Programming & Tools: Numerical programming, algorithms, use of MATLAB/Python/R
• Capstone: Senior project, undergraduate research or honours thesis

Entry requirements

Applicants should have a high school diploma or equivalent with a strong background in mathematics. Recommended preparation includes high school calculus (or AP Calculus) and courses in algebra and trigonometry. Admissions consider overall academic record and the strength of quantitative coursework; standardised tests may be optional depending on current university policies.

For transfer applicants and those coming from community colleges, completion of college-level calculus and at least one college linear algebra or discrete mathematics course is typically expected. Prospective students who lack some preparation are often advised to take bridging or introductory college mathematics courses before enrolling in higher-level mathematics modules.

Career prospects

Graduates with a computational mathematics background are well placed for careers that require both quantitative reasoning and computing skills. Common pathways include:

• Data science and analytics roles in tech, healthcare, retail and government
• Software development and engineering positions that focus on numerical methods or simulation
• Quantitative finance and risk analysis roles in banking and asset management
• Modelling and simulation in engineering, energy, and environmental sectors
• Actuarial work and statistical consulting
• Further study: graduate programmes in mathematics, applied mathematics, computer science, statistics or engineering

Many graduates start in industry roles that value programming and quantitative modelling, while others proceed to research or advanced degrees which lead to specialised academic or industrial research careers.

Why study at University of Kansas

The University of Kansas offers a mathematics programme with strong links between theoretical and applied work. The Department of Mathematics & Statistics provides a range of faculty expertise in numerical analysis, applied mathematics and computational methods, enabling undergraduate involvement in active research.

Students benefit from interdisciplinary collaboration across departments—particularly computer science, engineering and the natural sciences—and have access to campus computing resources and labs for numerical experimentation. Opportunities for undergraduate research, internships facilitated through career services and partnerships with regional employers help students develop practical experience and employable skills.

The Lawrence campus also supports a vibrant student community and a variety of extracurricular activities, including mathematics clubs and seminars, which complement classroom learning and encourage professional networking and peer learning.