Grow with us

We welcome students and collaborators interested in Earth system science, climate impacts, remote sensing, and data-intensive geoscience.

Grow with us

Recruiting status

We welcome students and collaborators interested in Earth system science, complex systems, and artificial intelligence. We particularly encourage applicants with strong backgrounds in physics, mathematics, atmospheric and climate science, geography, computer science, remote sensing, data science, or related quantitative disciplines, who are interested in exploring Earth system feedbacks, nonlinear dynamics, predictability, and AI-driven Earth system observation and prediction.

Good fit

If you are interested in understanding a changing Earth system through the integration of artificial intelligence, Earth observations, coupled model simulations, field investigations, and data-intensive methods—and in exploring feedbacks, nonlinear interactions, and predictability—this research group may be a good fit for you.

Research directions

  • Earth System Feedbacks and Resilience
  • Earth System Predictability and Climate Extremes
  • AI-Driven Earth System Observation and Prediction

Expected background

  • Strong quantitative thinking
  • Scientific curiosity
  • Interdisciplinary mindset
  • Programming and scientific computing
  • Machine learning and AI
  • Numerical modeling
  • Remote sensing and Earth observation
  • Large-scale data analysis
  • Earth and atmospheric sciences
  • physics
  • mathematics
  • computer science
  • Motivation to explore complex Earth system problems

What to prepare

  • A concise note about research background and interests
  • CV or academic profile
  • Relevant papers
  • projects
  • code
  • or writing samples when available

Collaborations

Collaboration inquiries should describe the shared research question, available data or methods, and the intended academic output.

Contact path

Email the group with your background, research interests, and the questions you hope to explore. Keep the note specific enough to show fit with the group's current research directions.