Postdoctoral Fellow: AI-Driven Severe Weather Modeling

Argonne National Laboratory; United States; On-site; USD 72,879 - 121,465; Full time

Benefits offered by this job

Comprehensive benefits package

Collaborative workplace environment

Opportunities for scientific discovery

Job summary

Argonne National Laboratory is seeking a highly motivated postdoctoral researcher to advance severe weather prediction through advanced modeling techniques and AI/ML approaches. The role focuses on high-resolution Earth system modeling to analyze convective storms, contributing to crucial research aimed at improving predictability.

The ideal candidate will have a recent Ph.D. in Atmospheric Science with strong programming skills and expertise in numerical modeling. This position offers a dynamic work environment focused on impactful scientific discovery.

Qualifications

• Ph.D. completed within the past 0-5 years in Atmospheric Science or a related field.
• Demonstrated expertise in convective storms or severe winds.
• Ability to work independently and in a team environment.

Responsibilities

• Conduct high-resolution model simulations of convective storms.
• Collaborate closely with scientists in the Earth system science community.
• Publish research findings in peer-reviewed journals.

Skills

Numerical modeling

High-performance computing

AI/ML methods in model development

Programming (Python, Fortran, C++)

Data analysis techniques

Statistical methods

Excellent scientific writing

Strong oral communication

Team collaboration

Education

Ph.D. in Atmospheric Science or a related field

Tools

C++

GPU-based systems

Job description

Argonne National Laboratory is seeking a highly motivated postdoctoral researcher to advance severe weather prediction through advanced modeling techniques and AI/ML approaches. The role focuses on high-resolution Earth system modeling to analyze convective storms, contributing to crucial research aimed at improving predictability.

The ideal candidate will have a recent Ph.D. in Atmospheric Science with strong programming skills and expertise in numerical modeling. This position offers a dynamic work environment focused on impactful scientific discovery.