Mesonet Post-Doctoral Researcher
Listed on 2026-07-17
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Research/Development
Data Scientist
Postdoctoral Research Assistant
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.
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 QualificationsDoctoral 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 InformationTo 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 before submitting a full application.
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