Hybrid Physical Scientist - Marine Seasonal Forecast Dev

American Meteorological Society; College Park (MD); Hybrid; USD 110,000 - 150,000; Full time

Benefits offered by this job

Personalized career growth plans

E-Verify employer

Job summary

Lynker Technologies is seeking a Physical Scientist - Seasonal Forecast System Developer to support NOAA/OMD in Marine and seasonal forecasting. You will contribute to the Seasonal Forecast System and AI/ML prediction models, working onsite at NCWCP in Riverdale Park and remotely for part of the week.

The role requires advanced knowledge of S2S, ensemble methods, and modern programming (FORTRAN, Python) with strong HPC and Git experience. A Master/PhD in a related field is required.

Qualifications

• Master or PhD in atmospheric sciences or related field with 1–2 years experience in global coupled ensemble forecast systems, sub-seasonal to seasonal prediction, and AI/ML models.
• Proven ability to develop ensemble forecasts and AI/ML solutions for NWP.
• Experience with FORTRAN and Python programming, and HPC environments.
• Familiarity with Git/GitHub and modern software development practices.
• Strong communication skills for interdisciplinary collaboration and results reporting.

Responsibilities

• Develop global coupled NWP models and marine forecast systems.
• Design and evaluate UFS-based seasonal forecasting frameworks.
• Conduct retrospective ensemble experiments and re-forecasts.
• Apply AI/ML methods for seasonal and marine forecasting.

Skills

S2S prediction

AI/ML in NWP

FORTRAN

Python

HPC

Git/GitHub

Communication

Team collaboration

Education

Master's or PhD in atmospheric sciences / meteorology / oceanography / related physical science

Job description

Lynker Technologies is seeking a Physical Scientist - Seasonal Forecast System Developer to support NOAA/OMD in Marine and seasonal forecasting. You will contribute to the Seasonal Forecast System and AI/ML prediction models, working onsite at NCWCP in Riverdale Park and remotely for part of the week.

The role requires advanced knowledge of S2S, ensemble methods, and modern programming (FORTRAN, Python) with strong HPC and Git experience. A Master/PhD in a related field is required.