Dear Colleagues,

We are excited to invite you to submit abstracts for contributed oral presentations at the APS March Meeting Symposium on Machine Learning for Electronic Structure, Properties, and Dynamics of Molecules and Materials. This symposium, organized by Michele Pavanello, Mark Tuckerman, and Will Glover, will take place from March 3 to March 8, 2024, in Minneapolis, Minnesota.

Our distinguished invited speakers include: Michele Ceriotti, Pavlo Dral, Rafael Gómez-Bombarelli, Christine Isborn, Heather Kulik, Klaus-Robert Müller, and Anatole von Lilienfeld

Key Topics Include:

• Advancements in Quantum Machine Learning
• ML-Based Density Functionals for DFT Simulations
• Machine Learning in Ab-initio Dynamics
• Prospects and Challenges of Current ML Models

We encourage researchers from all stages of their careers to submit abstracts for contributed talks. Share your latest findings, insights, and discoveries related to machine learning in electronic structure and materials science. 

Abstract submission details are available at https://march.aps.org/ with deadline October 20.

The sorting category is: 16.01.04 Machine Learning for Electronic Structure, Properties, and Dynamics of Molecules and Materials

We look forward to welcoming you to Minneapolis in March 2024 for what promises to be an engaging and informative symposium. Your participation will contribute to the ongoing discussion of the promises and potential challenges of current ML models and help shape the future of this dynamic research field.

Should you have any questions or require further information, please do not hesitate to contact us at [email protected]