Mathematical and Computational - Science Engineering Track
The Bachelor of Science in Mathematical and Computational Science – Science Engineering Track at University of Stanford offers students a comprehensive program combining advanced mathematics, computational methods, and engineering principles. In the early years, students build a strong foundation in calculus, linear algebra, discrete mathematics, and introductory programming, alongside courses in physics and applied sciences. These foundational courses foster analytical thinking, problem-solving skills, computational proficiency, and quantitative reasoning, enabling students to understand complex systems and apply mathematical concepts to real-world engineering problems. Through rigorous coursework, laboratory exercises, and collaborative projects, learners develop the critical skills necessary for advanced computational modeling and analysis.
As students progress, they engage with higher-level topics in numerical analysis, scientific computing, optimization, data structures, and engineering applications. The program emphasizes research-driven projects, computational simulations, and interdisciplinary problem-solving. Through seminars, capstone projects, and independent research, students refine their research methodology, computational expertise, analytical reasoning, and technical competence, preparing them for innovative careers in engineering, technology, and computational science. By graduation, students possess the mathematical, computational, and engineering skills required to tackle complex problems in both academic and professional contexts.
Key information
Key Facts
- Program Title: Mathematical and Computational - Science Engineering Track
- 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 Sciences
• Calculus and Linear Algebra
• Introduction to Programming and Computational Thinking
• Physics for Science and Engineering
• Discrete Mathematics
• Writing and Research in Computational Sciences
Year 2 – Core Mathematical and Computational Studies
• Differential Equations and Mathematical Modeling
• Data Structures and Algorithms
• Numerical Analysis
• Probability and Statistics for Engineering
• Seminar: Computational Problem Solving
Year 3 – Advanced Computational and Engineering Applications
• Scientific Computing and Simulation
• Optimization and Operations Research
• Engineering Applications of Computational Methods
• Advanced Algorithms and Complexity
• Electives in Applied Mathematics or Engineering
Year 4 – Capstone and Research Project
• Senior Thesis or Research Project
• Advanced Seminar in Computational Science
• Computational Modeling and Data Analysis
• Interdisciplinary Applied Projects
• Specialized Electives in Mathematical and Computational Science
Career Opportunities
Graduates of this program are prepared for careers in computational science, engineering, data analysis, software development, research, and academia. The curriculum emphasizes analytical reasoning, technical proficiency, problem-solving skills, and computational expertise, equipping students to pursue roles as computational engineers, data scientists, software developers, quantitative analysts, or research scientists. The program also provides a strong foundation for graduate study in applied mathematics, computer science, engineering, or interdisciplinary computational research. With a solid combination of theoretical knowledge and practical application, graduates are capable of designing and implementing computational solutions for complex technical and scientific challenges.
Why Choose This Program
This program is ideal for students who wish to combine rigorous mathematical training with computational and engineering applications. Its curriculum emphasizes critical thinking, quantitative analysis, computational modeling, and problem-solving competence, providing learners with both theoretical knowledge and hands-on experience. Through advanced courses, research projects, and interdisciplinary collaboration, students develop the skills to model complex systems, analyze large datasets, and implement engineering solutions effectively. Graduates leave with the expertise, professional readiness, and confidence necessary to pursue careers in computational science, engineering, technology, or advanced academic study, making meaningful contributions to scientific and technical innovation.
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
