Program Areas

Mathematics & Physical Sciences
Life Sciences
Autism Research Initiative
Simons Collaborations
Flatiron Institute
Science, Society & Culture
Multidisciplinary Programs

Funding

Funding Opportunities
Independence Awards
Policies and Procedures
Award Instructions
Simons Award Manager (SAM) FAQs and Videos

News

Announcements
Articles
Videos
What We’re Reading

Events

Presidential Lectures
Presents

About

About Us
Media Relations
Brand Portal
Leadership
Annual Report
Diversity, Equity & Inclusion
Careers
Summer at Simons
Contact Us
COVID-19

Simons Foundation

CCQ

Research
Publications
News
Events
Software
About
People

Home
Flatiron Institute
Center for Computational Quantum Physics
News

Heather Kulik: (Not quite) doomed to fail: machine learning to detect and overcome limitations of DFT for strongly correlated materials

August 5, 2021

Video Thumbnail

Advancing Research in Basic Science and MathematicsSubscribe to Flatiron Institute announcements and other foundation updates

About Us
Funding
News
Events
Annual Report
Contact Us
Career Opportunities

Follow Us

© Simons Foundation
Terms and Conditions
Privacy Policy
Image Credits

Program Areas
Program Areas
Funding
News
Events
- Presidential Lectures
- Presents
About
About

© Simons Foundation
Terms and Conditions
Privacy Policy
Image Credits

We use cookies to analyze web traffic and to improve your browsing experience; full details are in our privacy policy. Please agree to accept cookies from our site.AGREE