The bad thing about ERC grants (and ERC Synergy grants) is that usually very low information is available about them. Which is quite contradictory, since being those (supposed to be) the best and visionary projects in a certain field, they should be open to the masses who should learn a lot from them. Among the Synergy grants approved just yesterday, there is this one, which is certainly of interest for hydrologists, which aims to focus of new models of the global Earth. Actually somewhere in the press, was mentioned the word hybrid (physics-ML) modelling of observation of Earth system, which means that it is not all about machine learning (this is the ML above) but also the integration of these models with traditional equations solvers. The colleague who proposed the project are, as you can verify, all brilliant top scientists: Veronika Eyring (a modeller, climatologits, GS ), Markus Rechstein (a biogeo-chemist with modelling abilities, @Reichstein_BGC, GS), Gustau Camps-Vall (head of a signal processing and visualisation group, @isp_uv_es, GS) and Pierre Gentine ( Hydrologic Cycle, Land-Atmosphere-interactions, turbulence, convection, soil moisture, looking at the global scale, GS).
Browsing (click on the GS above), their impressive paper production, one can have an idea of what their project can be, but some particular papers, as this one, recent, in Nature, can be considered as a “proof of concept” of the project, I guess.
More divulgative material can be found, instead here. Mark Reichstein explain also some of the concepts of using deep learning in the Global Cycle Cycles in Stockholm here.
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