Hybrid Seasonal Forecast System Developer & AI/ML Scientist

Lynker Corporation

College Park (MD)

Hybride

USD 110 000 - 150 000

Plein temps

Il y a 9 jours

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Avantages offerts par ce poste

Healthcare benefits
PTO and holidays
401(k) with company matching
ESOP

Résumé du poste

Lynker Corporation is seeking a Seasonal Forecast System Developer to support the NOAA NCWCP in Riverdale Park, MD, focusing on marine components and AI/ML prediction models for global coupled seasonal forecasting.

The role offers a hybrid schedule: 2 days per week in-office at NCWCP/College Park and 3 days remote. The candidate will collaborate with OMD scientists and external partners to advance SFS and UFS infrastructure.

Qualifications

  • Advanced knowledge of S2S prediction and coupled SFS development.
  • Experience in ensemble-based forecasting and retrospective experiments.
  • Proficiency in FORTRAN and Python.
  • Experience with HPC and scripting.
  • Familiarity with modern software development practices and version control.

Responsabilités

  • Develop and evaluate global coupled ensemble forecasting systems.
  • Work with OMD scientists and collaborators on SFS improvements.
  • Design experiments including retrospectives and reforecasts.
  • Explore initial and model uncertainties and probabilistic forecasts.
  • Communicate results clearly in written and oral form.

Connaissances

S2S prediction
Ensemble forecasting
AI/ML for NWP
FORTRAN
Python
HPC
Git / GitHub
communication
teamwork
attention to detail

Formation

Master's or PhD in atmospheric sciences or related physical science

Outils

Git
GitHub

Description du poste

Lynker Corporation is seeking a Seasonal Forecast System Developer to support the NOAA NCWCP in Riverdale Park, MD, focusing on marine components and AI/ML prediction models for global coupled seasonal forecasting.

The role offers a hybrid schedule: 2 days per week in-office at NCWCP/College Park and 3 days remote. The candidate will collaborate with OMD scientists and external partners to advance SFS and UFS infrastructure.

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