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MIT Short Course - Predictive Multiscale Materials Design

Markus J. Buehler's picture

We at MIT, welcome you to join us this summer, in person, for a hands-on design-to-product Predictive Multiscale Materials Design course from June 13-17, 2022. All course registrants will receive an MIT certificate upon completion.

In this condensed five-day course, you will participate in hands-on clinics, design studios and labs 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 discover how to integrate advanced technologies to drive the development of next-generation smart materials. You will enhance your ability to leverage the most in-demand areas of materials engineering:

  • Multiscale modeling
  • Machine learning
  • Bio-inspired design
  • Additive manufacturing, and
  • Nanotechnology.

Embedded in the dynamic environment at MIT, alongside international peers, 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.

The course involves pre- and post-course elements. Personal office hour sessions will be held to gain feedback several weeks after the program, providing the opportunity to ask in-depth questions after you have had a chance to reflect on the course material.

More information and sign-up:

Course instructor: Markus Buehler, McAfee Professor of Engineering, MIT

A select number of Academic Fellowships are available upon request - please express your interest and send your CV to mbuehler@MIT.EDU



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