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Data-Enabled Computational Engineering and Science
The Master of Science in Data-Enabled Computational Engineering and Science (DECES) at Brown University is a one-year, full-time program that bridges advanced computing, data science, and engineering analysis to address modern scientific and industrial challenges. Designed for students with backgrounds in engineering, applied mathematics, or physical sciences, the program focuses on equipping them with the computational skills and modeling techniques needed to simulate, optimize, and interpret complex systems. Through a rigorous curriculum, students learn to apply machine learning, high-performance computing, and numerical analysis to problems in fields such as materials design, fluid dynamics, energy systems, and structural analysis.
This interdisciplinary program takes full advantage of Brown’s research strengths in industrial and systems engineering, applied mathematics, and computer science. Students work closely with faculty on real-world case studies and data-intensive projects that require deep integration of domain knowledge and computational tools. The curriculum encourages analytical precision and creative problem-solving, while also emphasizing reproducible science and scalable algorithms. With a balance between theory and application, the program prepares graduates to become computational leaders who can innovate at the intersection of data, simulation, and engineering design.
Key information
Key Facts
- Program Title: Data-Enabled Computational Engineering and Science
- Degree Type: Master of Science
- Duration: 1 year
- Mode of Study: Full-time, On Campus
- Application Deadline: 01 February 2026
- Location: Brown University, United States
- Field of Study: Industrial & Systems Engineering
- Language of Instruction: English
Program Structure
Semester 1 – Foundations in Computational Science and Data Modeling
- Scientific Computing and Numerical Methods
- Statistical Learning and Data Analysis
- Fundamentals of Continuum Mechanics or Thermodynamics
- Programming for Computational Engineering
Semester 2 – Applied Systems and Simulation
- High-Performance Computing in Engineering
- Optimization and Uncertainty Quantification
- Capstone Project in Computational Science
- Elective: Multiphysics Modeling, AI in Engineering, or Systems Design
Career Opportunities
Graduates of the DECES program are highly valued in industries where data-driven modeling and simulation are critical to performance, innovation, and scalability. Typical career paths include computational engineer, R&D scientist, systems analyst, and machine learning engineer within sectors such as aerospace, energy, materials science, automotive, and high-tech manufacturing. Many also work in national laboratories, research institutes, or advanced engineering firms, developing digital twins, predictive models, and simulation pipelines. The program's strong foundation in both theory and coding prepares graduates to contribute to the design and optimization of complex engineered systems, using computational tools to reduce costs, enhance safety, and accelerate product development. Some graduates pursue doctoral study, while others transition directly into roles where they lead cross-functional teams in engineering innovation and computational research.
Why Choose This Program
This program offers a rare and powerful blend of computational depth, engineering application, and data fluency, designed to meet the growing demand for engineers who can model, simulate, and optimize complex systems in data-rich environments. At Brown, students benefit from close interaction with faculty engaged in cutting-edge research, as well as access to advanced computing facilities and collaborative lab spaces. The curriculum emphasizes not only technical rigor but also practical experience through projects that reflect real-world engineering challenges. The one-year format is ideal for ambitious learners who want to rapidly elevate their skills and step into high-impact roles. Whether you're interested in simulation-driven design, predictive modeling, or the future of intelligent systems, this program gives you the tools, mindset, and momentum to lead innovation at the frontier of engineering and data science.
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
