Mesonet Post-Doctoral Researcher

Job Summary

The Louisiana State Mesonet, within the School of Sciences at the University of Louisiana Monroe (ULM), is seeking applications for a postdoctoral research assistant with experience in high-resolution numerical models and data assimilation. The researcher will assist the mesonet program in generating real-time, high-resolution weather forecasts across the broader Southeastern United States and the Lower Mississippi River basin region and using/testing mesonet observations to improve model forecasts. The researcher may be tasked with implementing specific model output to support project objectives and partner/stakeholder requests. This is a full-time, 12-month position currently funded for 1-year at a competitive salary with a full benefits package. Employment extension beyond the first year is possible based on funding availability and a favorable formal review.

Duties and Responsibilities

Deploy and maintain a high-resolution weather modeling system for generating real-time forecasts

• Use Louisiana mesonet data to test how the observations improve the model’s initial conditions to lead to improved weather forecasts
• Verify and validate model forecast output against LSM observations to evaluate forecast skill and identify areas for improvement over time
• Generate real-time forecasts of precipitation and soil moisture, backed by mesonet observations, across the Lower Mississippi River basin region
• Document model configurations, data assimilation workflows, and operational procedures to ensure continuity of the forecasting system
• Collaborate with the mesonet team, partners, and other stakeholders to turn ideas into possible model output and/or additional applications
• Any other duties as needed at the request of the Mesonet Executive Director

Minimum Qualifications

Doctoral degree in Meteorology, Atmospheric Science, or a related technical discipline

• Experience deploying and running high-resolution numerical weather prediction models to generate real-time forecasts, preferably including MPAS
• Experience with data assimilation
• Familiarity with Linux and high-performance computing (HPC) environments, including job scheduling and operational workflow management
• Strong problem-solving skills, ability to work in a collaborative environment, and a desire to learn new technologies are a must
• Excellent oral and written communication skills
• A record of high-quality, peer-reviewed publications
• Proficiency in Python or equivalent scripting languages for model implementation, output analysis, and data visualization
• Ability to work a flexible schedule

Supplemental Information

To apply please submit a cover letter, CV/resume, and a completed ULM application for employment.

Interested candidates are encouraged to reach out to Dr. Todd Murphy at murphy@ulm.edu before submitting a full application.