.png&w=1920&q=75)
Applied Mathematics
The Bachelor of Arts in Applied Mathematics at Brown University offers a comprehensive and flexible four-year curriculum that integrates mathematical theory with real-world applications. The program is designed for students who are passionate about solving complex problems using quantitative reasoning, mathematical modeling, and computational techniques. Core areas of study include differential equations, probability, numerical methods, and optimization, all taught within a context that encourages interdisciplinary exploration. This degree enables students to understand and develop mathematical tools that address challenges across fields such as engineering, biology, finance, and data science.
What sets this program apart is its adaptability within Brown’s open curriculum. Students can combine applied mathematics with complementary interests like computer science, economics, or public health, shaping their academic paths to match their personal goals. The department fosters a collaborative environment, offering research opportunities, seminars, and access to cutting-edge technology. Whether preparing for graduate study or direct entry into industry, students leave the program with strong analytical thinking, problem-solving abilities, and a deep understanding of how mathematics drives innovation in the modern world.
Key information
Key Facts
- Program Title: Applied Mathematics
- Degree Type: Bachelor of Arts
- Duration: 4 years
- Mode of Study: Full-time, On Campus
- Application Deadline: 05 January 2026
- Location: Brown University, United States
- Field of Study: Applied Mathematics
- Language of Instruction: English
Program Structure
Year 1 – Mathematical Foundations
- Single-Variable and Multivariable Calculus
- Introduction to Programming
- Linear Algebra
- Foundations of Applied Mathematics
Year 2 – Core Methods and Applications
- Differential Equations
- Probability and Statistics
- Discrete Mathematics
- Introduction to Numerical Analysis
Year 3 – Advanced Topics and Electives
- Optimization Methods
- Stochastic Processes
- Applied Linear Algebra
- Elective: Mathematical Modeling or Data Science
Year 4 – Synthesis and Specialization
- Capstone Project or Independent Study
- Partial Differential Equations
- Elective: Machine Learning or Computational Biology
- Seminar in Applied Mathematics
Career Opportunities
Graduates of this program are well-equipped for careers in industries that require analytical rigor, computational expertise, and quantitative insight. They often work in data analysis, financial modeling, actuarial science, and software development, where they apply mathematical techniques to optimize processes, interpret data, and inform strategic decisions. Others find roles in biotechnology, engineering consulting, or environmental science, contributing to modeling and simulation tasks. The program also provides a strong foundation for advanced study in applied mathematics, statistics, operations research, or interdisciplinary graduate programs, preparing students to lead in research-intensive or innovation-driven careers.
Why Choose This Program
This program combines deep mathematical training with the freedom to pursue interdisciplinary interests, offering a tailored and intellectually rich undergraduate experience. Brown’s open curriculum empowers students to explore how applied mathematics intersects with fields like computer science, economics, and biology, all while developing highly transferable skills. The department supports student growth through accessible faculty, advanced coursework, and active research communities. With an emphasis on real-world problem solving and conceptual clarity, this degree equips students with the tools, mindset, and versatility to succeed in both academic and professional environments that demand precision, logic, and creativity.
Contact Information
For further information, please contact the admissions office at:
Phone: +1 401 863 1000
Email: admissions@brown.edu
Address: University of Brown, Providence, RI 02912, United States
