Teams at Ai2

Develop an open-source AI-powered, physics-informed climate model for improved multidecadal forecasting. Adapt NeuralGCM training pipelines for Google Cloud and NVIDIA GPUs, document and distribute code, couple the model with an ML ocean model, test performance in unseen climates, collaborate through software engineering practices, and create tutorials for the climate modeling community.

Lead research and evaluation of an AI-powered, physics-informed climate model designed for accurate multidecadal forecasts. Develop training and testing cases, implement model improvements for generalization to unseen climates, couple atmospheric, oceanic, land, and sea-ice systems, publish findings, contribute open-source code, collaborate with researchers, and mentor interns.

Develop an AI-powered, physics-informed hybrid climate model for accurate multidecadal forecasting. Responsibilities include coupling NeuralGCM with an ML ocean model, designing physically constrained learning approaches, testing model performance in unseen climates, publishing research, contributing to open-source code, collaborating with climate scientists and engineers, and mentoring postdocs and interns.