Ursinus College

What you'll study

The Computational Mathematics track builds a strong foundation in pure and applied mathematics while emphasising computational techniques, numerical methods and scientific programming. You will study a sequence of core mathematics courses alongside supporting computer science and statistics units.

• Core mathematics: calculus sequence, linear algebra, differential equations, probability and mathematical statistics, and real analysis or advanced calculus.
• Computational and applied units: numerical analysis, scientific computing, computational linear algebra, mathematical modelling, optimisation and methods for differential equations.
• Programming and supporting subjects: courses in programming (typically Python and/or MATLAB), data structures or introductory computer science, and applied statistics or data analysis.
• Electives and breadth: options in discrete mathematics, abstract algebra, topology, stochastic processes, machine learning, computational biology or finance depending on interests and availability.
• Capstone and research: a senior seminar, capstone project or independent research experience supervised by faculty, often involving computational projects, data analysis or simulations.

The programme is delivered in small classes with a mix of lectures, problem sessions and lab-based computing work. Students are encouraged to take internships, collaborative research projects and study abroad to broaden applied experience.

Entry requirements

Admission to the Mathematics programme at Ursinus College follows the college’s general undergraduate entry process. Successful applicants typically demonstrate strong performance in high-school mathematics (algebra, geometry, precalculus and, where available, calculus) and have good overall academic records.

• Completion of secondary school with strong grades in mathematics.
• Recommended preparation: precalculus and calculus if available, plus experience with problem-solving and quantitative coursework.
• Evidence of interest in computational work, such as prior programming experience, relevant coursework or extracurricular projects, is helpful but not always required.
• Ursinus operates an admission policy that gives weight to academic record, teacher recommendations, personal statement and extracurricular involvement; standardised tests may be submitted but are not required for all applicants.

Career prospects

Graduates with a Computational Mathematics emphasis are prepared for a range of careers that value quantitative reasoning and computing skills. Typical roles include:

• Data analyst, data scientist or business intelligence analyst — applying statistical methods and computational tools to extract insight from data.
• Software developer or engineer — especially in roles that require strong algorithmic and mathematical foundations.
• Quantitative analyst or risk analyst in finance — modelling, simulation and optimisation for markets and risk management.
• Actuarial analyst — with further professional exams, working on insurance and financial risk problems.
• Technical roles in engineering, biotechnology or scientific research — developing simulations and numerical models.
• Further study — many graduates pursue graduate degrees in mathematics, computer science, statistics, engineering, or related fields.

Ursinus’s emphasis on undergraduate research, internships and close faculty mentoring helps students build portfolios of projects and practical experience that are attractive to employers and graduate programmes.

Why study at Ursinus College

Ursinus is a liberal arts college that offers small class sizes, a high level of faculty access and a collaborative learning environment. Mathematics students benefit from personalised mentorship, opportunities for independent research and interdisciplinary work with computer science, physics and economics departments.

• Undergraduate research: faculty-led research projects and senior theses give students hands-on experience in computational projects and modelling.
• Teaching and mentorship: small seminars and problem sessions mean more individual feedback and closer support for mastering challenging material.
• Practical experience: connections with local employers, internship programmes and career services help students gain workplace experience and professional contacts.
• Computing resources: access to labs and software commonly used in numerical computing and data analysis supports coursework and independent projects.
• Liberal arts context: a broad curriculum encourages communication, critical thinking and interdisciplinary perspectives valuable to mathematicians working in applied settings.

Together, these features make Ursinus a strong choice for students who want a mathematically rigorous education combined with practical computational skills in a close-knit college setting.