University of Findlay

What you'll study

The Computational Mathematics programme combines a traditional mathematics core with courses in numerical methods, scientific computing and applied modelling. Students follow a coherent four-year curriculum that includes general education, major requirements and electives, with emphasis on both theory and hands-on computation.

• Core mathematics: Calculus sequence, linear algebra, differential equations and real analysis to build a solid theoretical foundation.
• Computational and applied courses: Numerical analysis, scientific computing, computational linear algebra, optimisation and applied modelling using real-world data.
• Statistics and probability: Probability theory, mathematical statistics and data analysis to support stochastic modelling and inference.
• Programming and software: Instruction and practice in languages and tools common in computational mathematics such as Python, MATLAB, R and appropriate high-performance computing concepts.
• Electives and cross-disciplinary options: Discrete mathematics, mathematical modelling, machine learning, mathematical biology or courses from computer science and engineering to tailor the degree to specific interests.
• Capstone and experiential learning: A senior capstone or thesis project, often involving faculty-mentored research, interdisciplinary collaboration or an internship with local industry or research groups.

Entry requirements

Applicants should hold a high-school diploma or equivalent with a strong preparation in secondary mathematics including algebra, geometry and pre-calculus or calculus. Typical applications include high-school transcripts and a personal statement outlining interest in mathematics and computation. The university considers standardised tests according to its current admissions policy; applicants from other colleges or universities should submit official post-secondary transcripts. Prospective students without recent formal preparation may be admitted with placement testing or recommended preparatory courses.

Career prospects

Graduates are prepared for a range of careers that rely on quantitative and computational skills. Many move into roles in data analysis, software development, scientific computing, quantitative modelling, actuarial work, operations research and technical consulting. The degree also provides a strong foundation for graduate study in mathematics, statistics, computer science, engineering, finance or other STEM fields. Internship and capstone experiences frequently lead to professional opportunities in industry, government and research organisations.

Why study at University of Findlay

The University of Findlay offers a personalised learning environment with small class sizes and close faculty mentorship, enabling hands-on training in computational tools and methods. Students benefit from access to computing laboratories, opportunities for undergraduate research and internships with regional employers. The programme encourages interdisciplinary collaboration with computer science, physics and engineering courses and supports students preparing for professional certifications or further graduate study. Advising and career-services support help students translate classroom skills into practical experience and job placement.