M.S. in Data Science for Chemical Engineering and Materials Science

The M.S. in Data Science for Chemical Engineering and Materials Science degree bridges disciplinary expertise in chemical engineering and materials science with data and computational science. It aims to educate the next generation of chemical engineers and materials scientists that will be able to work seamlessly with digital technologies.

The program core provides fundamental knowledge of statistical and data analysis, machine learning, and optimization, as well as their application in chemical, biological, and materials science and engineering problems. Elective courses allow students to specialize in artificial intelligence, high performance computing, systems engineering, automation and robotics, or data analytics, depending on their specific interests and needs. Students have the option to complete a capstone project under the supervision of CEMS faculty, possibly in collaboration with faculty from other departments or industry advisors.

Testimonials from MS in Data Science for CEMS program alumni:

"The MS in Data Science for CEMS offers a well-balanced opportunity to gain a broad perspective on the field while also delving deeply into specific areas of interest. I highly recommend this program to incoming students, especially Ph.D. students in CEMS who are interested in pursuing computational research."  

"The program opened new opportunities that weren't available to me previously, as well as providing more specialized training that allowed me to focus on what interests me. The faculty and staff helped greatly to tailor the program in a way that helps me learn the most I can."

For more information on the curriculum program, please visit the M.S. in Data Science for Chemical Engineering and Materials Science curriculum page.

View our admissions page for information about application requirements for this program.