In an era where artificial intelligence (AI) reshapes industry from healthcare to manufacturing, the Master of Science in Artificial Intelligence Engineering-Chemical Engineering (MS in AIE-ChE) degree program from Carnegie Mellon University (CMU) equips you to grasp cutting-edge AI knowledge and integrate it into complex chemical engineering challenges.
Offered by CMU's College of Engineering and the Department of Chemical Engineering, the MS in AIE-ChE teaches fundamentals of AI and machine learning (ML) and chemical engineering principles. Learn how to combine both of these capabilities to work on projects from crafting autonomous systems for self-driving cars to optimizing decision-making processes in industrial settings.
Ranked fifth in U.S. News & World Report's prestigious list of best graduate engineering programs, CMU has long been a leader in applying AI to solve engineering challenges. Propel your career into a unique and high-demand trajectory with our three-semester Master's in Artificial Intelligence Engineering-Chemical Engineering degree program.
Why earn a master's degree in Artificial Intelligence Engineering-Chemical Engineering at Carnegie Mellon?
Combine the power of AI and chemical engineering
As the impact of machine learning and AI continues to grow, industries seek workers well-versed in both engineering disciplines and machine learning. Explore how to merge fundamental chemical engineering principles with the transformative capabilities of AI as a student at CMU.
The MS in AIE-ChE helps you master the art of integrating AI from a project's inception to create more efficient procedures and find practical solutions. Learn how to simultaneously design a system's functionality and its supporting AI mechanisms to produce more adaptable and resilient systems.
Learn interdisciplinary skills
Acquire the skills to drive innovation at the crossroads of artificial intelligence and chemical engineering with the MS in AIE-ChE. Our curriculum teaches you:
- The fundamental methods and algorithms at the core of modern machine learning
- AI systems, workflows, and tool chains
- Methods and applications for deep neural networks
- Security, privacy, and other ethical and societal challenges
- Engineering constraints that AI-orchestrated systems must operate within
- Numerical approaches that address complex problems in the realm of chemical engineering applications
- Process simulation software for modeling chemical and reactive systems
- Analysis and modeling of physical and chemical processes
- Process systems modeling
- AI methods for solving challenging chemical engineering problems
Supportive environment for chemical engineering students
CMU and the Department of Chemical Engineering take pride in creating a supportive environment for graduate students. Our collaborative community encourages close professional relationships with faculty and fellow students across engineering disciplines.
Many MS in AIE-ChE students join the Chemical Engineering Graduate Student Association (ChEGSA) and the Chemical Engineering Master's Student Association (ChEMSA), which help students build friendships and provide networking events throughout the year.
"The interdisciplinary MS in AIE-ChE program effectively enhances programming and AI skills while providing a holistic understanding of the intersection between AI and chemical engineering. The guidance from advisors is exceptional, fostering an environment conducive to creativity and innovation. I highly recommend this program for ambitious individuals seeking to excel in the dynamic field of AI and chemical engineering."
Saaksshi Jilhewar, MS in AIE-ChE, fall 2023
Curriculum for the Master's in Artificial Intelligence Engineering-Chemical Engineering
The MS in AIE-ChE is a full-time program that incorporates coursework and research. You can complete the 120-unit degree program in three semesters. You will take:
Four AIE core courses (42 units)
- 14-813 Special Topics: Systems and Tool Chains for AI Engineers (12 units)
- 24-787 Machine Learning & AI for Engineers (12 units)
- 24-788 Introduction to Deep Learning (6 units)
- 24-784 Special Topics: Trustworthy AI (12 units)
Three of the following ChemE core courses (36 units minimum)
- 06-623 Mathematical Modeling of Chemical Engineering Processes (12 units)
- 06-625 Chemical & Reactive Systems (12 units)
- 06-663 Analysis & Modeling of Transport Phenomena (12 units)
- 06-665 Process Systems Modeling (12 units)
Four electives (42 units total)
- You can personalize your master's experience with curated electives that fit seamlessly into our curriculum. Browse examples of electives that align with student interests.
- At least one of the electives must have a significant project component (at least 12 units) and be approved by the department. You may complete a comprehensive research project with faculty to meet this requirement.
39-699 Career & Professional Development for Engineering Master's Students
- Three units but does not count towards total minimum required units
"In a world where AI has revolutionized various domains, I am excited about utilizing its potential in chemical engineering research. The MS in AIE-ChE program at CMU emerges as the perfect choice for individuals like myself who are fascinated by the intersection of machine learning and process systems engineering. The program is unrivaled in offering opportunities to collaborate with world-renowned researchers. Within the department's nurturing environment, I have found abundant opportunities for personal and professional growth."
Saroj Sathish, MS in AIE-ChE, fall 2023
Careers and outcomes for AI engineering and chemical engineering students
Whether students pursue academia or industry, the MS in AIE-ChE degree program uniquely equips them for the future of engineering data science. With the ability to integrate engineering domain knowledge into AI solutions, they discover abundant opportunities in high-demand career paths. Examples of relevant industry positions include:
- Advanced analytics research scientist
- Battery engineer
- Data scientist/process engineer
- Deep learning research engineer
- Neuroengineer
- Senior 3D process engineer
- Senior bioinformatics quality engineer
See post-graduation salaries and destination information for recent CMU Chemical Engineering graduates.
Admissions and application deadlines
If you have a bachelor's degree in chemical engineering or a related discipline and an interest in the intersection of AI and engineering, we encourage you to apply to the Master's in Artificial Intelligence Engineering-Chemical Engineering program.
You should be proficient in:
- Introductory knowledge of probability/statistics, including probability distributions, conditional probability, and maximum likelihood estimation
- Linear algebra topics such as matrix operations and linear transformations
- Programming (Python preferred) for data analysis
We accept applications and enrollment for both spring and fall semesters.
- Fall term of entry deadline: January 31
- Spring term of entry deadline: September 1
Take the next step
Combine the power of AI and machine learning with domain expertise in chemical engineering with a Master's in Artificial Intelligence Engineering-Chemical Engineering from Carnegie Mellon University.