MIT Predictive Multiscale Materials Design Short Course - June 2-6, 2025
June 2–6, 2025, MIT Campus, Cambridge, MA
June 2–6, 2025, MIT Campus, Cambridge, MA
The School of Civil and Environmental Engineering at Cornell University (Ithaca campus) invites applications for a tenure-track faculty position in the broad area of dynamics related to the mechanics of structures and materials. Our definition of structures is broad and includes buildings, bridges, dikes, wind turbines, and solar devices/solar panels.
We are interested in applicants whose research is related to any of the following or related areas:
• Material and/or structural response to dynamic loading arising from wind, waves, blast, seismic waves
We are looking for a PhD student for a research project on textile modelling and characterization. In this project, the main purpose is to develop a multi-scale textile modelling framework that allows accurate simulation of textile manufacturing processes such as yarn unwinding from a bobbin, weft insertion during weaving, stitching and tufting. Besides a strong numerical research focus, there is also an experimental research track focusing on advanced mechanical testing of textile materials and their connections, both on lab-scale and industrial scale (e.g.
TL;DR: Back on MIT campus, in person, with technical lectures, group work, interactive labs and clinics, networking sessions, and participant talks! Materials design has endless applications in countless industries, and its impact is growing especially at the nexus of creating more sustainable, functional and efficient materials platforms. MIT Predictive Multiscale Materials Design short course will be held during the week of June 12-16, 2023, at MIT. Participants will earn an official MIT certificate.
In this course you will fully learn how to incorporate new materials informatics methods into your own material modeling, analysis and design processes in order to capitalize on recent AI breakthroughs, such as language models (e.g. GPT-3, BERT, LaMDA, etc.), DNA and protein models (e.g., AlphaFold), graph neural networks applied from molecular to macroscale structures, and a host of methods adapted for computer vision including diffusion models (as used in DALL-E 2 or Imagen), specifically for the analysis, design and modeling of materials. The course involves a mix of lectures, hands-on labs and clinics for an immersive experience. Participants will learn fundamentals and techniques to deploy machine learning in materials development and gain first-hand understanding of state-of-the art tools for varied applications ranging from data mining to inverse design. We will cover scales from the molecular to the continuum.
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.
https://professional.mit.edu/course-catalog/predictive-multiscale-mater…
We have open Ph.D. positions in my group at the University of Houston (UH) this Fall or Spring 2022. The general area of research is the mechanics of material failure. Of particular interest, is understanding how microstructures influence damage and fracture processes in advanced materials including metals and polymers. We formulate theoretical frameworks to assess and predict material behaviors at different length-scales via computational modeling and simulations. We closely collaborate with experimental groups.
The Department of Mechanical Engineering at the Indian Institute of Science, Banglore is celebrating its 75th year by hosting distinguished speakers.
This month's talk will be delivered by Prof Dennis Kochmann (ETH Zurich).
Title: Learning from the building blocks of nature in the design of periodic architected materials
Date: Februrary 17, 2021
Time: 16:30 Indian Standard Time (06:00 New York, 12:00 Zurich, 19:00 Beijing)