Lead Computational Scientist, Earth System Data Assimilation

University Corporation for Atmospheric Research; United States; On-site; USD 129,000 - 167,000; Full time

Benefits offered by this job

Health insurance

Dental

Retirement plan

Leave plans

Tuition assistance

Job summary

University Corporation for Atmospheric Research seeks a Computational Scientist V to join CPAESS with NOAA's OMD. The role advances ocean-ice data assimilation and integrates sea-surface observations to improve atmospheric-ocean balance and forecast skill.

You will lead complex computational research, guide multidisciplinary teams, and communicate results to sponsors and the scientific community while developing scalable HPC software and novel numerical methods.

Qualifications

• Minimum of BS and 15 years experience, or MS and 11 years, or PhD and 7 years, or equivalent.
• Expert in numerical methods, parallel computing, HPC architectures.
• Proven ability to lead teams and communicate with stakeholders.
• Experience with data assimilation and model development.

Responsibilities

• Lead design and execution of complex computational research projects in Earth system science.
• Develop numerical methods and algorithms for HPC environments.
• Direct teams and contribute to proposal development and publications.
• Collaborate with senior leadership and sponsors for strategy and program planning.

Skills

Numerical methods

High-performance computing

Parallel computing

Data assimilation

JEDI framework

Programming

Mentoring

Scientific communication

Education

B.S. in a scientific field

M.S. in a scientific field

Ph.D. in a scientific discipline

Tools

JEDI

GFS

NOAA systems

Job description

University Corporation for Atmospheric Research seeks a Computational Scientist V to join CPAESS with NOAA's OMD. The role advances ocean-ice data assimilation and integrates sea-surface observations to improve atmospheric-ocean balance and forecast skill.

You will lead complex computational research, guide multidisciplinary teams, and communicate results to sponsors and the scientific community while developing scalable HPC software and novel numerical methods.