Santa Clara University

What you'll study

The programme emphasises applied analysis, numerical methods and computational modelling, combining rigorous mathematical foundations with practical computing skills. Core topics typically include numerical analysis, partial differential equations, applied linear algebra, optimisation and probability and statistics for applied contexts. Students also study scientific computing, mathematical modelling of physical and engineering systems, and may take electives in machine learning, data science, stochastic processes, dynamical systems and control theory.

Instruction commonly mixes lectures, problem-solving seminars and computer-based projects. Students normally complete a capstone requirement such as a substantial project or applied thesis supervised by faculty; some pathways allow course-only completion with a culminating comprehensive project. Coursework emphasises Matlab, Python and other industry-standard tools for simulation, data analysis and algorithm implementation.

Entry requirements

Applicants are expected to hold a bachelor's degree in mathematics, applied mathematics, engineering, physics, computer science or another quantitatively rigorous discipline. A strong background in calculus, linear algebra, differential equations and introductory real analysis or advanced calculus is typically required. Prior programming experience and familiarity with numerical methods are advantageous.

• Official transcripts demonstrating relevant undergraduate coursework.
• Academic references or letters of recommendation from instructors or employers who can speak to quantitative preparation and potential for graduate study.
• A personal statement outlining academic interests, relevant experience and goals for the degree.
• Proof of English proficiency for international applicants (accepted tests include TOEFL or IELTS).

The programme may consider applicants with non-traditional backgrounds who demonstrate quantitative ability through coursework or professional experience. Standardised tests such as the GRE may be optional or recommended depending on the admissions cycle; consult the university for current guidance.

Career prospects

Graduates of the MSc in Applied Mathematics move into a range of technical and research-oriented careers. Common roles include data scientist, quantitative analyst, machine learning engineer, computational scientist, operations research analyst and software developer focused on numerical or scientific computing. Graduates also work in finance, engineering, energy, biotech, and technology companies, often in positions that require modelling, algorithm development and large-scale data analysis.

The degree also provides solid preparation for doctoral study in applied mathematics, statistics or related fields for those pursuing an academic or research career.

Why study at Santa Clara University

Santa Clara University offers this programme within a liberal arts context and benefits from its location in Silicon Valley, providing proximity to high-technology firms, startups and research labs that value applied mathematical skills. The university is known for small class sizes and close faculty mentorship, which supports project-based learning and opportunities for collaborative research.

Students can draw on interdisciplinary resources across engineering, computer science and business faculties, access computing facilities and pursue internships through robust local industry connections. The Jesuit educational tradition also emphasises ethical and socially responsible approaches to technical work, which many students find valuable as they apply quantitative skills in professional settings.