Mathematical and Computational Science
The Bachelor of Science in Mathematical and Computational Science at University of Stanford provides students with an integrated education in mathematics, computation, and data analysis. In the first year, students develop a solid foundation in calculus, linear algebra, discrete mathematics, programming, and computational thinking. These courses cultivate analytical reasoning, problem-solving skills, quantitative proficiency, and research methodology, enabling students to approach complex mathematical and computational problems with rigor. Through lectures, lab exercises, and project-based learning, learners gain hands-on experience in algorithm development, numerical analysis, and data modeling.
As students progress, the curriculum emphasizes advanced mathematical theory, computational modeling, data science, and algorithmic design. Independent research projects, seminars, and advanced coursework refine students’ technical expertise, critical evaluation, applied problem-solving, and computational proficiency. The honors curriculum encourages students to tackle original research, develop innovative computational algorithms, and apply mathematical models to real-world problems. By graduation, students are prepared for careers in data science, computational research, financial modeling, software development, or advanced graduate study in mathematics, computational science, or related disciplines.
Key information
Key Facts
- Program Title: Mathematical and Computational Science
- Degree Type: Bachelor of Science
- Duration: 4 years
- Mode of Study: Full-time, On Campus
- Application Deadline: 05 January 2026
- Location: Stanford University, United States
- Field of Study: Computational Mathematics
- Language of Instruction: English
Program Structure
Year 1 – Foundations in Mathematical and Computational Science
• Calculus and Linear Algebra
• Introduction to Computer Programming
• Discrete Mathematics and Logic
• Writing and Research in Mathematics
• Introduction to Computational Modeling
Year 2 – Core Mathematical and Computational Studies
• Advanced Calculus and Differential Equations
• Probability and Statistics
• Data Structures and Algorithms
• Computational Mathematics and Modeling
• Seminar: Research Methods in Computational Science
Year 3 – Advanced Applications
• Numerical Analysis and Scientific Computing
• Data Science and Machine Learning
• Independent Research Projects
• Optimization and Mathematical Modeling
• Electives in Advanced Mathematics or Computational Fields
Year 4 – Capstone and Honors Project
• Senior Thesis or Independent Research Project
• Advanced Seminar in Computational Mathematics
• Applied Computational Modeling Projects
• Interdisciplinary Mathematical Research
• Specialized Electives in Mathematical and Computational Science
Career Opportunities
Graduates of this program are prepared for careers in data science, computational research, financial modeling, software development, and applied mathematics. The curriculum develops analytical skills, technical proficiency, problem-solving abilities, and research expertise, enabling students to pursue roles as data scientists, quantitative analysts, computational researchers, algorithm developers, or software engineers. Hands-on experience through independent research projects, computational modeling, and applied coursework ensures that graduates can tackle complex, real-world problems using mathematical and computational tools. Additionally, the program provides strong preparation for graduate study, equipping students with the skills needed to specialize in mathematics, computational science, or interdisciplinary research at the graduate level.
Why Choose This Program
This program is ideal for students who wish to combine rigorous mathematics with advanced computational techniques to solve complex scientific, technological, and data-driven problems. Its structure emphasizes critical thinking, quantitative reasoning, research methodology, and applied problem-solving, providing students with both theoretical knowledge and practical experience. Through seminars, independent research, computational modeling projects, and advanced coursework, learners develop the skills to design algorithms, analyze large datasets, model real-world systems, and contribute to technological innovation. Graduates leave with the expertise, confidence, and professional readiness to pursue careers in data science, computational mathematics, software development, finance, or advanced academic study, while also gaining adaptability for emerging challenges in computational and quantitative disciplines.
Contact Information
For further information, please contact the admissions office at:
Phone: +1 650 000 0000
Email: admissions@standord.edu
Address: University of Standord, 450 Serra Mall, Stanford, CA 94305, United States
