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Sacbar

Senior Atmospheric Scientist

northern, KY

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Job 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

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

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