Description

About the Role

We are seeking an exceptional PhD-level Atmospheric Scientist or Meteorologist with expertise in severe convective storms and tornado dynamics to join our research team. This position focuses on advancing the prediction and understanding of severe weather through cutting-edge analysis, numerical modeling, and machine learning approaches.

The successful candidate will work in a high-impact research environment focused on improving severe weather forecasting, warning lead time, and understanding of storm-scale processes. The role offers opportunities to collaborate with operational forecasting offices, national research programs, and interdisciplinary teams working at the forefront of meteorological science.

This position is ideal for researchers passionate about bridging the gap between academic research and operational forecasting.

Key Responsibilities

Conduct advanced research on severe convective storms, mesocyclones, and tornado intensity prediction
Analyze radar, satellite, and in-situ atmospheric datasets to investigate storm-scale dynamics
Develop and apply machine learning and statistical models to anticipate severe weather hazards
Perform analysis using numerical weather prediction models and storm-resolving simulations
Collaborate with forecast offices, national weather programs, and research institutions
Publish findings in peer-reviewed scientific journals
Present research at national and international conferences
Develop reproducible analysis tools using Python and modern scientific computing environments
Participate in field campaigns and observational research projects

Requirements

Required Qualifications

Ph.D. in Atmospheric Science, Meteorology, or a closely related discipline
Demonstrated research experience in severe convective storms or tornado dynamics
Strong background in radar meteorology, atmospheric dynamics, or storm-scale processes
Experience with Python or other scientific programming languages
Proven ability to conduct independent research and publish results
Excellent written and verbal communication skills

Preferred Qualifications

Experience applying machine learning or artificial intelligence to meteorological problems
Familiarity with convection-allowing models and numerical simulations
Experience with tools such as WRF, GR2Analyst, GEMPAK, BUFKIT, or ArcGIS
Experience working with operational meteorology teams or forecasting centers
Participation in field campaigns or observational meteorology projects