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.