MIT Predictive Multiscale Materials Design Short Course - June 2-6, 2025

MIT Predictive Multiscale Materials Design Short Course

June 2–6, 2025, MIT Campus, Cambridge, MA

TL;DR: An in-person, high-impact week of deep technical lectures, hands-on labs, interactive clinics, networking events, and participant talks—all focused on the future of materials design using tools like physics-based generative AI, multi-agent AI, molecular modeling, and precision manufacturing. Participants will earn an official MIT certificate. Academics can apply for a fellowship that covers part of the course fee. Please contact mbuehler@MIT.EDU. 

More details, including a course schedule: https://professional.mit.edu/course-catalog/predictive-multiscale-materials-design 

The short course features many interactive elements, allowing participants to learn in a dynamic environment. The course includes technical lectures, group work, interactive labs, clinics and participant talks. It is rewarding not only to learn, but to network with peers & MIT researchers. You will gain hands-on exposure about multiscale modeling, additive manufacturing, scientific machine learning, and smart bio-inspired materials and products. The course is designed to help you to accelerate and optimize your atomically precise material design and manufacturing through the use of large-scale computational modeling and molecular dynamics, material informatics, and artificial intelligence. You will enhance your ability to leverage the most in-demand areas of materials engineering, and learn how to strategically use:

• Predictive Multiscale Modeling – Bridge atomic-level insights to macroscopic material performance.
• AI for Science – Use LLMs, multi-agent AI, and generative AI for data mining, materials discovery and simulation.
• Bio-Inspired Design – Create materials that mimic nature’s resilience and adaptability.
• Additive Manufacturing – Design and fabricate materials atom-by-atom using 3D printing.
• Nanotechnology – Engineer function and performance at the smallest scales.

The course involves pre- and post-course elements. Key components include a pre-course lecture as preparation, detailed lecture notes, a carefully curated set of reading materials, codes and algorithms, strategic recipes, overview materials, and two post-course office hours for in-depth discussions with the instructor. The course if taught for an audience with diverse background ranging from researcher, manager, VP or VC.

Deeply embedded in the dynamic environment at MIT, alongside peers from around the world, you will gain insights into the science, technology, and state-of-the-art computing methods being used to fabricate innovative materials from the molecular scale upwards. Through lectures and hands-on labs and clinics, you will learn how to construct, in a bottom-up manner, atomically precise products through the use of molecular design, predictive modeling, and manufacturing, allowing the fabrication of a vast array of advanced, innovative designs for a wide-range of applications. You will also learn how to access and utilize web-based machine learning tools for materials analysis, and cement your knowledge with a “from design to production” project, in which you will use AI and other computational methods to produce a custom 3D-printed smart material.

More information and sign-up: https://professional.mit.edu/course-catalog/predictive-multiscale-materials-design 

Instructor: Markus J. Buehler
McAfee Professor of Engineering
https://meche.mit.edu/people/faculty/mbuehler@mit.edu 
MIT