Physics-Informed Deep Learning for Molecular Properties

Project funded by Austrian Science Fund (FWF) (ESPRIT), research institution: Universität Wien. Approved FWF funding: EUR 349,732, as stated by the source. Runs 2027-03-01 to 2030-02-28 (status: pending). Keywords: Cheminformatics, Machine Learning, Quantum Chemistry, Physicochemical Property. Source: FWF Research Radar (FWF Open API) (national funding data, not CORDIS); selected because its keywords name quantum technology.

Original source.

Source: FWF Research Radar (FWF Open API), Austrian Science Fund (FWF). Retrieved 2026-10-28. Licence: CC0 1.0 (FWF Open API data). Selected metadata, adapted presentation; the publisher's record is authoritative. No endorsement by the source is implied. Licence: public domain dedication (CC0 1.0).

AI-assisted summary: The project "Physics-Informed Deep Learning for Molecular Properties" is funded by the Austrian Science Fund (FWF) with an approved budget of EUR 349,732, running from March 1, 2027, to February 28, 2030. It focuses on cheminformatics, machine learning, and quantum chemistry. Suggested technology pillar: simulation. Generated by AI from the public source text; it may contain errors and the original source is authoritative.