Argonne National Laboratory · 1 day ago
Postdoctoral Appointee - AI Foundation Models for Atmospheric Science
Lemont, IL
Full-time
Onsite
New Grad, Entry Level
$73K/yr - $121K/yr
0+ years expArgonne National Laboratory, a U.S. Department of Energy national laboratory located near Chicago, Illinois, has an opening for a highly motivated postdoctoral appointee in the Decision and Infrastructure Sciences Division. The role involves collaborating to evaluate and develop machine learning-based weather models, particularly using generative AI techniques, to improve weather forecasting capabilities.
EnergyNon ProfitSecuritySocial Impact
No H1B
U.S. Citizen Only
Responsibilities
Contributes technical expertise through analysis and support for programs and projects associated with machine learning, HPC, and computational problems related to earth system science and other dynamical systems
Development, evaluation, and applying machine learning/computational approaches, synthesis activities, computational tools, compiling results, preparing reports, publications, and documentation
In particular, this position is for projects related to applying and developing machine learning-based weather models for the S2S timeframe with an emphasis on generative AI techniques, evaluating such models, and working with a team of scientists interested in pushing the boundary of predictability
Qualification
Required
Recent or soon-to-be-completed PhD (completed within the last 0-5 years) in geophysical sciences, computer science, or machine learning with 0 to 2 years of experience
Knowledge of deep learning, PyTorch/JAX, and scaling deep learning models to large GPU-based machines
Technical knowledge in using HPC systems for visualization and analysis
Technical knowledge of large, dynamical systems (preferably the atmosphere)
Knowledge and experience in writing scientific code
Skills in clear, concise writing of technical papers, and interacting and communicating effectively with colleagues
Problem solving skills
Organizational skills and flexibility in coordinating a broad spectrum of activities
Knowledge of atmospheric dynamics, process scale models, and numerical computation techniques
Knowledge of data analysis
Knowledge of using atmospheric observational datasets, data assimilation techniques, and statistics
Familiarity subseasonal-to-seasonal modeling and or coupled atmosphere-ocean modeling
Ability to work and communicate with stakeholders from public and private sectors
A successful candidate must have the ability to model Argonne's Core Values: Impact, Safety, Respect, Integrity, and Teamwork
Benefits
Comprehensive benefits
Company
Argonne National Laboratory
Argonne National Laboratory conducts researches in basic science, energy resources, and environmental management.
1001-5000 employees
Funding
Current Stage
Late StageTotal Funding
$41.4MKey Investors
Advanced Research Projects Agency for HealthUS Department of EnergyU.S. Department of Homeland Security
2024-11-14Grant· $21.7M
2023-09-27Grant
2023-01-17Grant
Leadership Team
Paul Kearns
Laboratory Director
Venkat Srinivasan
Director, Argonne Center for Collaborative Energy Storage Science (ACCESS)
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