Argonne 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.
Machine learning (ML), specifically deep learning (DL), has been demonstrated to successfully predict the weather for 1-14 days with skill on par with numerical weather prediction at a fraction of the computational cost. Recently Argonne successfully implemented, AERIS, a state-of-the-art seasonal-to-subseasonal (S2S) weather model AI model. A successful candidate will collaborate with this group to evaluate AERIS at S2S scales, couple ocean component to the model, data assimilation and regional refinement. In particular, this position will utilize generative AI to create a calibrated ensemble system for S2S at high resolution (30-km) to deliver probabilistic weather forecasts beyond 14 days to allow for actionable, local-scale impacts on infrastructure and communities.
The ideal candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative AI methods as well as experience in atmospheric science, especially weather modeling, are particularly sought after. This is a one-year position that can be extended to two years that we want to fill immediately.
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.
Position Requirements
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.
Job Family
Postdoctoral
Job Profile
Postdoctoral Appointee
Worker Type
Long-Term (Fixed Term)
Time Type
Full timeThe expected hiring range for this position is $72,879.00-$121,465.00.
Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
Click here to view Argonne employee benefits!
As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.
