Marywood University

What you'll study

The Computational Mathematics programme builds a solid foundation in pure and applied mathematics while emphasising numerical methods, scientific computing and algorithmic thinking. Core topics include multivariable calculus, linear algebra, ordinary and partial differential equations, real analysis and discrete mathematics. Computational and applied coursework commonly covers numerical analysis, scientific computing, programming for mathematicians (Python, MATLAB or similar), data structures and algorithms, probability and mathematical statistics.

Students typically complete a combination of required major courses and electives, allowing specialisation through options such as numerical linear algebra, optimisation, computational modelling, mathematical biology, and stochastic simulation. The curriculum often culminates in a capstone project or senior thesis that applies computational techniques to a substantial problem, and students are encouraged to take laboratory or computing practicum courses and to participate in undergraduate research with faculty.

Entry requirements

Applicants should hold a high school diploma or recognised equivalent with a strong record in mathematics. Recommended preparatory courses include precalculus and calculus; familiarity with computer science or programming is advantageous but not always mandatory. Marywood considers the overall academic profile, so evidence of analytical coursework, letters of recommendation and a statement of purpose are useful.

For transfer applicants, college-level mathematics credit will be evaluated for placement. International applicants must meet academic equivalency requirements and demonstrate English language proficiency by recognised tests or institutional alternatives where required. Prospective students are advised to consult Marywood University's admissions office for current submission materials and any programme-specific prerequisites.

Career prospects

Graduates with a computational mathematics degree are prepared for roles that require quantitative reasoning and programming skills. Common career paths include data analyst, quantitative analyst, software or algorithm developer, operations research analyst, and roles in finance, engineering, technology firms and government agencies. The mathematical modelling and numerical methods training also provide a strong foundation for graduate study in applied mathematics, computer science, engineering, data science or statistics.

Students often gain professional experience through internships, research projects and collaborative work with faculty, which helps transition into entry-level positions or postgraduate programmes. Additional credentialing, such as industry certificates or advanced degrees, can broaden opportunities in specialised fields like machine learning, computational finance or scientific computing.

Why study at Marywood University

Marywood offers a personalised undergraduate environment with small class sizes and close faculty mentoring, which is valuable for developing mathematical maturity and research skills. The university’s liberal arts context means students receive a broad education alongside concentrated technical training, and there are opportunities to engage in interdisciplinary projects that pair mathematics with the natural sciences, engineering or business.

Facilities for computation and undergraduate research, a supportive career services office, and local industry and institutional connections in the Northeastern Pennsylvania region provide practical pathways to internships and employment. The department emphasises experiential learning—students can pursue capstone projects, summer research, and applied internships that translate classroom theory into computational practice.