|From||Laure Zanna <email@example.com>|
|Date||Sat, 23 Jan 2021 08:41:11 -0500|
We are looking for 1 project manager and 12 postdocs at several institutions as part of a new exciting international collaboration, M²LInES: Multiscale Machine Learning In coupled Earth System Modeling, with climate and data scientists from New York University, Princeton, GFDL, Columbia, LDEO, NCAR, MIT, CNRS-IGE, and CNRS-IPSL.
The overall goal of the project is to improve climate projections and reduce climate model biases, especially at the air-sea interface, using machine learning (ML). We will rely on data from a range of high-resolution (idealized and global) simulations and data assimilation products to deepen our understanding and improve the representation of subgrid physics in the ocean, sea-ice and atmosphere components of existing IPCC-class climate models. In addition, we will work on overcoming challenges related to ML for climate modeling including sampling efficiency, generalization, interpretability and uncertainty quantification. This is a highly collaborative project, and the researchers are expected to interact with different groups.
Visit https://m2lines.github.io/jobs/ for more info about the different positions available, and how to apply.
I would be grateful if you could share with any qualified candidates.
Professor of Mathematics & Atmosphere/Ocean Science, NYU
Courant Institute + Center for Data Science
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