Senior Atmospheric Scientist

Sacbar; Tallahassee, Northern (FL, KY); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Sacbar in the United States invites a PhD-level Atmospheric Scientist or Meteorologist to join a high-impact research team. The role focuses on predicting severe convective storms, tornado dynamics, and improving warning lead time through advanced analysis, modeling, and machine learning.

The successful candidate collaborates with national weather programs and forecast offices, publishes in journals, and develops reproducible Python-based analysis tools.

Qualifications

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

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

Skills

Python

Radar meteorology

Storm-scale dynamics

Independent research

Scientific communication

Education

Ph.D. in Atmospheric Science or Meteorology

Tools

WRF

GR2Analyst

GEMPAK

BUFKIT

ArcGIS

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