Big Data for Computational Chemistry: Unified machine learning and sparse grid combination technique for quantum based molecular design

Project funded by Swiss National Science Foundation (SNSF) (NRP 75 Big Data), grant 167186. Participating organisations named by the source: University of Basel. Runs 2017-02-01 to 2020-08-31. Keywords: Chemistry. Source: OpenAIRE Graph, from the funder's project data (collected by OpenAIRE on 2026-07-23); national funding data, not CORDIS.

Original source.

Source: OpenAIRE Graph: projects of national funders, OpenAIRE, from the project data of Swiss National Science Foundation (SNSF). Retrieved 2026-11-01. Licence: Creative Commons Attribution 4.0 (OpenAIRE Graph). Selected metadata, adapted presentation; the publisher's record is authoritative. No endorsement by the source is implied. Licence: Creative Commons Attribution 4.0 (CC BY 4.0).

AI-assisted summary: The project "Big Data for Computational Chemistry" focuses on machine learning and sparse grid techniques for molecular design, funded by the Swiss National Science Foundation from 2017 to 2020, with the University of Basel as a participating organization. Suggested technology pillar: computing. Generated by AI from the public source text; it may contain errors and the original source is authoritative.