Research Associate I – Machine Learning for Tropical Cyclones

About the role

The Cooperative Institute for Marine and Atmospheric Studies (CIMAS) at the University of Miami is hiring a full‑time Research Associate I. The position focuses on developing and applying machine‑learning techniques to improve the analysis and prediction of tropical cyclones using data from crewed and uncrewed reconnaissance missions.

Key responsibilities

• Design, implement, and evaluate machine‑learning models to estimate surface winds in tropical cyclones when direct observations are unavailable.
• Generate real‑time wind products for testing by the National Hurricane Center.
• Assess the impact of various observing platforms on cyclone analyses and forecasts using the NOAA Hurricane Analysis and Forecast System (HAFS).
• Run, tune, and verify hurricane model forecasts on high‑performance computing clusters.
• Manage, process, and visualize large observational datasets using modern programming tools.
• Document findings in progress reports, peer‑reviewed papers, and present at conferences.

Required profile

• Bachelor’s degree in Meteorology, Atmospheric Science, or a closely related field.
• Experience with tropical‑cyclone reconnaissance data and operational hurricane modeling.
• Proficiency in machine‑learning applications and high‑performance computing environments.

Required skills

• Machine learning
• Python programming
• JavaScript
• High‑performance computing
• NOAA Hurricane Analysis and Forecast System (HAFS)
• Data management and visualization

What we offer

• Opportunity to work with leading researchers and NOAA scientists on cutting‑edge tropical‑cyclone research.
• Access to state‑of‑the‑art computing resources and observational datasets.
• Supportive academic environment that values collaboration and professional growth.