Russian Science Foundation grant number 23-13-00332, 2023 – 2025, 7 Mill. RUB per year, on сonstruction of phase diagrams from first principles using machine learning for two-component and three-component metallic systems. PI: Alexander Shapeev.
Russian Science Foundation grant number 22-73-10206, 2022 – 2025, 6 Mill. RUB per year, on development of machine-learning interatomic potentials with magnetic degrees of freedom. PI: Ivan Novikov.
Past Grants:
Russian Science Foundation grant number 18-13-00479, 2018 – 2022, 30 Mill. RUB, on application of machine learning to constructing interatomic interaction models. PI: Alexander Shapeev.
Joint Russian Foundation for Basic Research and German Science Foundation grant number 20-53-12012, 15 Mill. RUB, 2020 – 2022, on Machine learning the thermodynamics of complex materials with ab initio accuracy [Mach-Initio]. Skoltech PI: Alexander Shapeev (German PIs: Blazej Grabowsky and Fritz Koermann)
Russian Foundation for Basic Research grant number 20-03-00833, 3.75 Mill. RUB, 2020 – 2022, on Ring Polymer Molecular Dynamics and Interatomic Potentials with Active Learning: Quantum Effects in Astrochemical Reactions in the Gas Phase. The project is lead by Ivan Novikov.
Swiss National Science Foundation grant number 191680, ~5 Mill. RUB, 2020-2021 on Fast algorithms for accurate crystal defect simulations: Towards computer-aided materials design. PI: Max Hodapp.
Skolkovo Foundation, Next Generation Program 2016-7/NGP (a joint Skoltech-MIT joint project), 37.5 Mill RUB, 2017-2020 on Machine Learning Elastic Strain Engineering. Skoltech PI: Alexander Shapeev (MIT PI: Ju Li).