Chemical Engineering - Data and Computational Science
The Master of Science in Chemical Engineering – Data and Computational Science is an intensive program designed for students who want to integrate chemical engineering principles with advanced data science, computational modeling, and process optimization. The curriculum emphasizes the application of quantitative methods, simulation techniques, and predictive analytics to solve complex engineering problems. Through this program, students develop computational modeling, data analytics, process optimization, and engineering research skills, preparing them to design efficient chemical processes, analyze large datasets, and apply evidence based approaches to industrial and research challenges.
This one year, full time and on campus program immerses students in a rigorous academic environment where they collaborate with faculty experts, industry professionals, and researchers in chemical engineering and computational science. Coursework, simulation projects, and applied research allow learners to refine process simulation, machine learning for engineering applications, data driven decision making, and numerical methods for chemical systems. Graduates are prepared to contribute to innovation in chemical process design, optimize industrial operations, and implement data driven solutions in research labs, production facilities, and technology development settings.
Key information
Key Facts
- Program Title: Chemical Engineering - Data and Computational Science
- Degree Type: Master of Science
- Duration: 1 year
- Mode of Study: Full-time, On Campus
- Application Deadline: 15 February 2026
- Location: Columbia University, United States
- Field of Study: Chemical Engineering
- Language of Instruction: English
Program Structure
Semester 1 – Foundations of Chemical Engineering and Data Science
• Principles of Chemical Engineering
• Introduction to Data Science and Computational Methods
• Numerical Methods and Simulation Techniques
• Research Methods in Engineering
Semester 2 – Applied Data Analytics and Process Optimization
• Machine Learning Applications in Chemical Engineering
• Advanced Process Simulation and Modeling
• Data Driven Process Optimization
• Capstone Project in Chemical Engineering Data Science
Career Opportunities
Graduates of this program are prepared for careers in chemical, pharmaceutical, and materials industries, as well as research institutions and technology firms. Career paths include process engineer, data scientist for chemical processes, research engineer, computational modeling specialist, and industrial optimization consultant. Graduates are equipped to analyze complex chemical systems, develop predictive models, optimize manufacturing processes, and apply advanced computational techniques to engineering challenges. The program also prepares learners for innovation and leadership roles in data driven chemical engineering projects and research initiatives.
Why Choose This Program
Students choose this program because it combines chemical engineering expertise, advanced data science skills, computational modeling training, and applied research experience within a one year intensive framework. The curriculum emphasizes hands on learning through simulation projects, applied research, and collaboration with faculty and industry professionals, allowing learners to develop practical skills for optimizing chemical processes and solving complex engineering problems. Graduates gain the knowledge, confidence, and professional competencies necessary to integrate data driven approaches into chemical engineering practice, contribute to industrial innovation, and excel in research and technology development.
Contact Information
For further information, please contact the admissions office at:
Phone: +1 212 854 1754
Email: admissions@columbia.edu
Address: University of Columbia, Admissions Office, New York, NY, United States
