Computational Mechanics and Scientific Computing
The Computational Mechanics and Scientific Computing master’s program at University of Duke provides an interdisciplinary two-year curriculum focused on applying advanced computational methods to engineering and environmental problems. Students gain hands-on experience with numerical modeling, simulation, and high-performance computing while learning to address complex challenges in mechanics, materials science and environmental systems. The program combines rigorous theoretical training with practical applications, allowing learners to analyze, model and optimize engineering processes using state-of-the-art computational tools. Its structured approach ensures graduates develop both analytical rigor and technical expertise for professional or research-focused careers.
Participants benefit from access to modern computational laboratories, experienced faculty mentorship and collaborative research opportunities. The curriculum emphasizes numerical simulation, computational modeling, mechanics analysis and applied engineering, enabling learners to translate theoretical concepts into practical solutions. Through coursework, design projects and applied research, students develop critical thinking, problem-solving and technical proficiency. This combination of advanced theory and practical application equips graduates to contribute effectively to engineering design, environmental solutions and scientific computing projects.
Key information
Key Facts
- Program Title: Computational Mechanics and Scientific Computing
- Degree Type: Master of Engineering
- Duration: 2 years
- Mode of Study: Full-time, On Campus
- Application Deadline: 18 March 2026
- Location: Duke University, United States
- Field of Study: Environmental Engineering
- Language of Instruction: English
Program Structure
Semester 1 – Foundations of Computational Mechanics
• Applied Mechanics and Continuum Theory
• Numerical Methods for Engineers
• Computational Modeling Fundamentals
• Scientific Computing and Programming
Semester 2 – Advanced Simulation & Applications
• Finite Element Analysis
• Computational Fluid Dynamics
• Applied Mechanics Laboratory
• Seminar in Engineering Computation
Semester 3 – Specialized Research & Modeling
• Multiscale Modeling and Materials Simulation
• Environmental Systems Analysis
• Elective in Specialized Computational Topic
• Applied Research Project / Lab Rotation
Semester 4 – Capstone & Thesis Integration
• High-Performance Computing Applications
• Optimization and Computational Design
• Independent Research / Master’s Thesis
• Seminar in Scientific Computing
Career Opportunities
Graduates of this program are prepared for professional and research roles that require expertise in computational methods, mechanics and environmental modeling. Common career paths include computational engineer, mechanical modeling specialist, environmental simulation analyst and scientific computing researcher. Additional opportunities exist in engineering firms, research institutions, environmental agencies, technology companies and academia, where advanced computational skills are essential for problem-solving and innovation. The program also provides a strong foundation for those pursuing doctoral studies in computational mechanics, applied mathematics or engineering. By integrating theoretical knowledge with practical simulation experience, graduates are well-equipped to contribute to engineering projects, research initiatives and technological innovation.
Why Choose This Program
This two-year master’s program is ideal for students seeking a rigorous, computational and applied approach to mechanics and engineering. The curriculum emphasizes numerical modeling, scientific computing, applied mechanics and project-based research, ensuring learners develop technical expertise alongside practical problem-solving skills. Students engage in hands-on projects, faculty-guided research and seminars that enhance their ability to analyze, simulate and optimize engineering systems. The program’s structured, interdisciplinary design prepares graduates for careers in computational engineering, environmental analysis and scientific research, offering a clear pathway to professional and academic success.
Contact Information
For further information, please contact the admissions office at:
Phone: +1 (919) 684-8111
Email: admissions@duke.edu
Address: University of Duke, Durham, North Carolina, United States
