Title: Data Driven Materials Discovery: From ML to Maker Space

Sunday, July 30th, 2023 to Friday, August 4th, 2023

 Rapid advances in materials data availability holds the promise of an accelerated, data-driven materials discovery future.  From July 30th to August 4th, 2023 PARADIM will host a summer school on data in materials sciences introducing machine learning and data science tools for crystal synthesis with a focus on new, data-driven approaches to planning and guiding projects for 2D, Interfacial, and Layered Materials. The school is divided into morning lectures and afternoon hands-on labs integrating computational tools with experimental PARADIM laboratory tools.  

The hands-on lab activities are aimed to demonstrate the potential of ML to accelerate experimental quantum materials discovery through design for targeted properties. Students will use PARADIM facilities throughout the school to make and test materials based on the approaches discovered through the ML models they build. The curriculum includes computational materials design, high-throughput experimentation, closed-loop systems, and the development of autonomous methods empowered by AI/ML to create laboratories of the future and accelerated materials discovery.

As a reminder, for in-person attendees, computational work will use SciServer and GitHub. Please bring your laptop and create free accounts on SciServer ( https://apps.sciserver.org/login-portal/register ) and GitHub ( https://github.com/join ) before arrival. Please send us your usernames for each as soon as you have them. If you do not have a laptop, please let us know at paradim@jhu.edu so we can make alternative arrangements for you.

Apply now.  Space is limited. (Closed)

Join the 2023 JHU Summer School Webinar

Documents and Tutorials from 2023 summer school

PARADIM 2023 Summer School JHU: Sunday, July 30th, 2023 to Friday, August 4th, 2023