University of New Haven

What you'll study

The Computational Mathematics major combines core mathematical theory with numerical analysis, scientific computing and applied modelling. You will study calculus, linear algebra, differential equations and real analysis alongside computational-focused modules such as numerical methods, scientific programming, algorithm design and mathematical modelling. Coursework emphasises hands-on use of programming languages and software commonly used in industry and research (for example Python, MATLAB and numerical libraries), plus laboratory or project-based classes that apply mathematical techniques to problems in engineering, physical sciences, finance and data analysis.

• Core mathematics: Calculus sequence, Linear Algebra, Ordinary and Partial Differential Equations, Real Analysis or Advanced Calculus.
• Computational and applied modules: Numerical Analysis, Scientific Computing, Computational Linear Algebra, Mathematical Modelling and Simulation.
• Programming and algorithms: Introduction to Programming for Scientists, Data Structures and Algorithms, Computational Geometry or High-Performance Computing topics.
• Electives and interdisciplinary options: Probability and Statistics, Mathematical Finance, Operations Research, Machine Learning, Optimization, or courses drawn from computer science, engineering and physical sciences.
• Capstone project or research experience: A senior project or practicum that integrates mathematical theory with computational implementation and real-world data or engineering problems.

The programme typically includes general education requirements and offers opportunities for independent study, undergraduate research with faculty, internships and collaborative projects with other departments.

Entry requirements

Applicants are normally expected to have completed a recognised secondary school qualification with strong performance in mathematics. Typical preparation includes at least one year of higher-level mathematics (for example calculus) and familiarity with algebra, trigonometry and basic statistics. Colleges may also look for evidence of analytical ability demonstrated through additional science, computer science or problem-solving courses.

Admissions often consider a combination of academic records, personal statement and references. Applicants without formal programming experience are still welcome provided they show strong mathematical aptitude; introductory programming courses are available in the first year. International applicants must meet the university's English language proficiency requirements.

Career prospects

Graduates with a degree in Computational Mathematics have a broad range of career options in sectors that rely on quantitative and computational skills. Common career paths include roles as data analysts, quantitative analysts, software developers, numerical modeller, operations research analyst, and roles in engineering, finance, technology, defence, healthcare analytics and scientific research. The strong programming and modelling components also prepare graduates for graduate study in mathematics, computer science, engineering, data science or related fields.

The University of New Haven’s connections with local industry, internship programmes and career services help students secure practical experience and employment opportunities upon graduation.

Why study at University of New Haven

The University of New Haven offers a hands-on approach to mathematical education with small class sizes, close faculty mentorship and opportunities for applied research and internships. The campus’s proximity to regional industries and research institutions provides avenues for collaborative projects and experiential learning. Students benefit from a curriculum that blends rigorous mathematical theory with modern computational practice, preparing them for technical careers or postgraduate study.

Additional support services, including academic advising, tutoring centres and career services, help students navigate coursework, secure internships and plan post-graduation pathways. The programme’s emphasis on practical computing skills and project-based learning makes it well suited for students seeking to apply mathematics in real-world, computational contexts.