Rice University

What you'll study

The programme builds a core of rigorous mathematics (calculus, linear algebra and differential equations) together with applied and computational topics that emphasise modelling, numerical methods and data analysis. Typical course areas include:

• Advanced calculus and real analysis foundations
• Ordinary and partial differential equations and dynamical systems
• Linear algebra, matrix analysis and numerical linear algebra
• Numerical analysis and scientific computing, including algorithm implementation
• Probability, statistical methods and stochastic modelling
• Optimization and control theory
• Applied topics and electives such as mathematical biology, computational fluid dynamics, financial mathematics, image analysis and machine learning
• Capstone experiences: a senior project or honours thesis and opportunities for independent study or research with faculty

Students work closely with faculty and can take interdisciplinary electives in computer science, engineering, physics and economics. Laboratory-style computing courses and programming assignments are typical, and students are encouraged to participate in undergraduate research, internships and team-based modelling projects.

Entry requirements

Admission to Rice is competitive and looks for a strong overall academic record with demonstrated quantitative ability. Typical preparation for this major includes advanced high-school mathematics (calculus and pre-calculus) and experience with problem-solving or mathematics competitions where available. For transfer or non-traditional applicants, successful candidates usually have college-level calculus and linear algebra already completed.

Successful applicants also present evidence of curiosity and initiative in mathematics or related fields — for example, research projects, programming experience, internships, or strong performance in advanced coursework. English language proficiency is required for applicants whose first language is not English, and applicants should consult Rice's admissions resources for application policies and supporting materials.

Career prospects

Graduates with an applied mathematics degree go on to a wide range of careers where quantitative modelling and computation are central. Common paths include:

• Data science and analytics roles in technology, healthcare, energy and retail
• Quantitative analyst and risk management positions in finance and insurance
• Software engineering and algorithm development, especially where numerical methods are used
• Engineering and technical roles that require modelling expertise (e.g. aerospace, mechanical, biomedical)
• Research and development in national laboratories, government agencies, and industry
• Academic careers and graduate study in applied mathematics, statistics, computer science, engineering or related fields

Rice’s location in Houston also provides proximity to energy, biomedical and aerospace industries, which many students use for internships and early-career opportunities. The programme’s strong computational training is valued by employers and graduate programmes alike.

Why study at Rice University

Rice offers a personalised undergraduate experience with small class sizes and close faculty contact, making it easy for applied mathematics students to pursue honours research and cross-disciplinary projects. The university’s collaborative environment encourages joint work with departments such as computer science, engineering, physics and economics, enabling customised study plans that match career goals.

Undergraduates benefit from Rice’s strong emphasis on research and hands-on learning, access to modern computing resources, and a residential college system that supports community and extracurricular engagement. The university’s connections with industries and research institutions in Houston create practical internship and employment pathways for students in applied mathematics.