University of Vermont

What you'll study

This programme builds a strong foundation in core mathematics while emphasising computational methods and their application. You will study calculus and advanced calculus, linear algebra, ordinary and partial differential equations, probability and mathematical statistics, and abstract mathematics such as real analysis and algebra. Computational and applied courses commonly include numerical analysis, scientific computing, algorithms, optimisation, mathematical modelling, and introductory machine learning.

Students typically combine core mathematics modules with computer science and data-focused electives to develop programming fluency (e.g. Python, MATLAB, or C++) and experience with numerical libraries, high-performance computing, and data visualisation. The curriculum often culminates in a capstone project or undergraduate research experience where you apply computational methods to problems drawn from science, engineering, finance or public policy.

• Core mathematics: calculus sequence, linear algebra, differential equations, real analysis
• Computational courses: numerical analysis, scientific computing, algorithms, optimisation
• Applied topics: mathematical modelling, statistics and probability, introductory machine learning
• Computing skills: programming, data structures, use of numerical libraries and HPC concepts
• Capstone / research: project-based work in collaboration with faculty or external partners

Entry requirements

Admission to the University of Vermont’s bachelor’s programmes normally requires a secondary school completion or equivalent. Prospective mathematics students should have a strong background in mathematics, typically including coursework in algebra, geometry and precalculus; preparation in calculus is strongly recommended. Schools will consider the overall academic record, strength of mathematics and science classes, and evidence of quantitative ability.

For international applicants, an equivalent secondary academic credential is required together with proof of English proficiency. Applicants with prior programming experience or coursework in computer science will be competitive for the computational emphasis. Transfer applicants should provide transcripts from prior post-secondary study and descriptions of completed mathematics courses for credit evaluation.

Career prospects

Graduates with a computational mathematics emphasis are well placed for careers that combine quantitative reasoning and programming. Common pathways include roles in data science and analytics, software and algorithm development, quantitative finance, operations research, computational engineering, and scientific computing. Many graduates move on to graduate study in mathematics, computer science, statistics, data science, or engineering, while others enter industry positions that value numerical modelling and problem-solving skills.

Internships, undergraduate research and cross-disciplinary coursework increase employability by providing applied experience. Employers range from technology and finance companies to government labs, research organisations and startups, as well as continuing into academic or professional training.

Why study at University of Vermont

The University of Vermont offers a supportive undergraduate environment with opportunities for close faculty mentorship, undergraduate research, and interdisciplinary collaboration. Students in computational mathematics benefit from links between the mathematics and computer science communities on campus, access to modern computing resources and lab facilities, and chances to work on real-world projects with faculty across science, engineering and policy fields.

UVM’s location and campus culture favour hands-on learning, internships with regional employers, and connections to broader research networks. The department emphasises both theoretical understanding and practical computational skills, preparing graduates for flexible careers or advanced study in a range of quantitative disciplines.