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Collaborative Research: CDS&E: Adaptive Uncertainty-Driven AI for Drug Discovery: A Conformal Prediction-Simulation Loop Approach

Collaborative Research: CDS&E: Adaptive Uncertainty-Driven AI for Drug Discovery: A Conformal Prediction-Simulation Loop Approach is a funding opportunity from NSF, closing July 31, 2029.

Funder
NSF
Funding
Grant / contract
Deadline
Jul 31, 2029
(1097d left)

Overview

Yihang Wang of Case Western Reserve University, and collaborator Lu Cheng of the University of Illinois Chicago, are supported to develop artificial-intelligence (AI) methods that quantify their own uncertainty and refine themselves through molecular simulation for more reliable computational drug discovery. The…

Collaborative Research: CDS&E: Adaptive Uncertainty-Driven AI for Drug Discovery: A Conformal Prediction-Simulation Loop Approach | Go Fund It Now