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.
