March 21, 2024, 1 p.m. | Alyssa Hughes

Microsoft Research www.microsoft.com

Senior Researcher Chang Liu discusses M-OFDFT, a variation of orbital-free density functional theory (OFDFT) that leverages deep learning to help identify molecular properties in a way that minimizes the tradeoff between accuracy and efficiency.


The post Abstracts: March 21, 2024 appeared first on Microsoft Research.

accuracy deep learning efficiency free functional identify microsoft microsoft research microsoft research podcast research researcher theory variation

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Reporting & Data Analytics Lead (Sizewell C)

@ EDF | London, GB

Data Analyst

@ Notable | San Mateo, CA