Case Western Reserve University

What you'll study

The Computational Mathematics pathway blends core mathematical foundations with courses in numerical analysis, scientific computing and algorithmic problem solving. Students take a sequence of calculus and linear algebra courses, probability and statistics, ordinary and partial differential equations, and applied analysis before specialising in computation‑focused topics.

• Core mathematical courses: Multivariable calculus, linear algebra, real analysis, and differential equations.
• Computational and applied topics: Numerical analysis, scientific computing, numerical linear algebra, numerical solution of PDEs, optimisation and computational modelling.
• Programming and software: Coursework and labs using Python, MATLAB, and experience with C/C++ or other compiled languages; high‑performance computing concepts and parallel programming for large‑scale computation.
• Probability and data: Probability theory, mathematical statistics, and elective courses in data analysis, machine learning or stochastic modelling.
• Capstone and research: An undergraduate capstone, project course or supervised research with faculty in applied mathematics, computational science or related departments; opportunities to collaborate on interdisciplinary projects with engineering, computer science, or medical research groups.
• General education and electives: Broader liberal‑arts requirements and elective choices allow students to gain domain knowledge (e.g. finance, biology, or physics) for application of computational techniques.

Students typically progress through a four‑year curriculum that combines classroom instruction, computational labs and project work; honours tracks or independent study are available for students seeking an intensive research experience.

Entry requirements

Applicants should demonstrate strong preparation in mathematics and analytical reasoning. Typical expectations include:

• A secondary school diploma or international equivalent with a strong record in mathematics. Prior coursework in calculus is highly recommended.
• Preparation or coursework in precalculus/advanced algebra and experience with problem solving; further credit or placement may be awarded for AP/IB or other recognised examinations in calculus or maths.
• Familiarity with programming is advantageous; applicants with experience in Python, MATLAB or similar languages will be well prepared for computational coursework.
• Competitive applicants often show evidence of quantitative aptitude through coursework, mathematics competitions, summer programmes, or related extracurricular activities. International applicants should meet the university's general language and credential requirements.

Admission is to the university; prospective majors should consult the Department of Mathematics for advising on specific major declarations, placement testing and course sequencing.

Career prospects

Graduates with a Computational Mathematics major are prepared for a range of analytical and technical roles. Common career paths include:

• Data scientist, data analyst or machine learning engineer in technology, healthcare, or finance.
• Quantitative analyst, risk modeller or algorithm developer in banking and investment firms.
• Software engineer or computational developer focusing on scientific and engineering applications.
• Operations researcher or optimisation specialist in logistics, manufacturing and public sector planning.
• Research assistant or technical specialist in national laboratories, hospitals and biotech companies where quantitative modelling is required.
• Further study in graduate programmes in mathematics, applied mathematics, statistics, computer science, engineering or business.

Internships, project experience and undergraduate research at Case Western Reserve University enhance employability by providing practical experience and industry connections in Cleveland and beyond.

Why study at Case Western Reserve University

Case Western Reserve University offers a strong mathematics department with particular strengths in applied and computational areas, and close interdisciplinary links with the Department of Computer Science, engineering schools and nearby medical research institutions. Students benefit from:

• Access to faculty active in computational mathematics and applied research, with opportunities for one‑on‑one mentoring and undergraduate co‑research.
• Interdisciplinary project opportunities that pair mathematical expertise with real‑world problems in engineering, finance, healthcare and data science.
• Computational resources and support for high‑performance computing projects and numerical experimentation.
• Proximity to a diverse industrial and clinical ecosystem in Cleveland, which supports internships, co‑ops and employment connections.
• A liberal‑arts informed curriculum that combines mathematical rigour with practical computational skills, preparing graduates for both industry roles and graduate study.