Masters Program: Data Science for Chemical Engineering and Materials Science
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.
- Learn more about the M.S. in Data Science for Chemical Engineering and Materials Science degree here:
- Interested in learning more about the M.S. in Data Science for Chemical Engineering and Materials Science? Watch a recording of a recent information session that addresses some basic questions about the program.
IPRIME: Data Driven Discovery and Design Program (4D)
The ever-increasing availability of data and computing power has led to rapid adoption of artificial intelligence and machine learning methods in a broad range of applications in cheminformatics, bioinformatics, and materials design. Data generated in these fields can be massive or sparse, time-varying or steady, low-dimensional or high-dimensional, discrete or continuous, low-fidelity or high-fidelity, uncertain and noisy, biased, and typically constrained by physical laws. The 4D program aims to address the above challenges and accelerate the application of data science in industry. More information can be found below: