Graduate students gain sophisticated technical skills and a comprehensive understanding of data-enabled computational engineering used in national laboratories and industries.
The School of Engineering at Brown is a world leader in several disciplines relevant to the Master of Science in Data- Enabled Computational Engineering and Science (DECES) program, including solid mechanics, materials science, fluid and thermal systems. Brown has one of the highest-ranked Applied Mathematics programs in the nation. Many of our stellar faculty in Engineering and Applied Mathematics are working on developing state-of-the-art numerical methods and machine learning approaches, with applications that are of particular relevance to the DECES ScM program. As such, Brown is uniquely positioned to offer the DECES ScM Program.
The DECES ScM program was designed for students interested in pursuing careers that involve advanced modeling and simulation in engineering and physical sciences. It may also be of interest to working professionals whose success on the job depends on their ability to competently perform high-fidelity engineering simulations with data assimilation and machine learning expertise.
Upon completion of the program coursework the students will:
- Gain the understanding of a significant role that advanced simulation plays in industry and national laboratories
- Develop an appreciation for the power of high-fidelity modeling and simulation in contemporary engineering design
- Gain technical knowledge of the foundational subjects in computational engineering, including nonlinear finite element analysis and the integration of physics-based modeling and data science
- Develop the necessary technical skills combined with machine learning expertise to knowledgeably carry out practical engineering-scale simulations
Students will take a total of eight courses to satisfy the degree requirements. To ensure breadth, students are expected to take a minimum of two courses in engineering, minimum of two courses in applied mathematics, and a minimum of two courses in data science/high-performance computing. Two additional courses must be taken to satisfy the program requirements.
Master of Science – Non-Thesis Option
Students are expected to complete the Master of Science – Non-Thesis program option in three semesters, taking three courses in the first and second semesters, and two courses in the third semester (i.e., the 3-3-2 model). One-year completion is also possible with students taking four courses in the first semester and four courses in the second (i.e., the 4-4 model). The maximum duration students may take to complete will be four semesters.
Master of Science – Thesis Option
Students are expected to complete the Master of Science – Thesis program option in three or four semesters. In the three-semester format, the students are expected to take three courses in the first semester, three in the second semester, and two in the third semester. However, in the second and third semesters, the students may sign up for a “Reading Research and Design” type class (i.e., ENGN 2980 or equivalent in APMA) to satisfy the eight-course requirement. In the four-semester model, students are expected to take three courses in the first semester, two in the second semester, two in the third semester, and one in the fourth semester. In both cases, the “Reading Research and Design” course may be counted up to two times toward the degree.
The master of science degree program in Data-Enabled Computational Engineering and Science is designed for students who have recently completed their bachelor’s degree (<5 years). Current Brown University seniors are encouraged to apply for a fifth-year master's degree.
If you have any questions regarding the application process for this program, please email firstname.lastname@example.org.
Required (not required for Brown fifth-year master’s applicants)
Required for any non-native English speaker who does not have a degree from an institution where English is the sole language of instruction or from a University in the following countries: Australia, Bahamas, Botswana, Cameroon, Canada (except Quebec), Ethiopia, Ghana, Ireland, Kenya, Lesotho, Liberia, Malawi, New Zealand, Nigeria, Zimbabwe, South Africa, Sierra Leone, Swaziland, Tanzania, Gambia, Uganda, United Kingdom (England, Scotland, Northern Ireland, Wales), West Indies, Zambia).
The TOEFL iBT Special Home Edition and the IELTS Indicator exam are accepted. Students from mainland China may submit the TOEFL ITP Plus exam.
Required. All applicants may upload unofficial transcripts for application submission. Official transcripts are ONLY required for enrolling students before class start. An international transcript evaluation (WES, ECE, or SpanTran) is required for degrees from non-U.S. institutions before enrollment.
Letters of Recommendations:
Three letters of recommendation
Bachelor’s degree in Engineering, Physical Sciences, Natural Sciences, or related subject
The strongest preference is given to those with an undergraduate GPA of at least 3.4
Early Admission Deadline
5th Year Deadline
Students must complete the 8 course requirements which include:
- A minimum of two courses in engineering
- A minimum of two courses in applied mathematics
- A minimum of two courses in data science/high-performance computing.
- Two additional courses must be taken to satisfy the program requirements.