专业介绍
Brown University’s on-campus master’s in data-enabled computational engineering and science equips you with technical skills and deep understanding needed for real-world applications in national laboratories and industries.
As a world leader in applied mathematics, solid mechanics, materials science and fluid and thermal systems, Brown’s School of Engineering is uniquely positioned to offer the master’s in data-enabled computational engineering and science program.
This computational engineering master’s program prepares you for Ph.D. study or a career at the forefront of advanced simulation, modeling and machine learning in engineering and physical sciences. Whether you’re a recent graduate, rising professional or an experienced engineer, you’ll master high-fidelity simulations, data assimilation and machine learning techniques essential for solving complex real-world problems.
This program offers the following degree with three track options:
- Master of Science (Sc.M.)
- Thesis (Coursework and thesis)
- Non-Thesis (Coursework only)
- Professional (Coursework and internship)
Through the highly-interdisciplinary curriculum, you’ll gain a deep understanding of the significant role that advanced simulation plays in industry and national laboratories, while acquiring technical skills in computational engineering and machine learning expertise. This includes mastering nonlinear finite element analysis and the integration of physics-based modeling with data science. You will become comfortable using all the established software programs (e.g., MATLAB, Python) and new software (e.g., TensorFlow).
During the program, you’ll work with accomplished faculty who are developing state-of-the-art numerical methods and machine learning approaches that are directly applicable to this program. The small cohort allows you to be advised by the leading faculty, develop strong long term relationships with your peers, receive Ph.D. and career application coaching, and obtain access to the Brown alumni network.