Postdoctoral Appointee – Scalable Simulation and AI/ML Workflows

at  Argonne National Laboratory

The Argonne Leadership Computing Facility (ALCF) is seeking a Postdoctoral Appointee to perform research and development of scalable workflow tools for coupling traditional HPC simulations with AI/ML.
This postdoctoral appointee will build upon work already being done at the Facility to enable such workflows and will contribute to the development and benchmarking of scalable solutions integrating parallel simulations with AI/ML distributed training and inferencing on leadership systems, such as the Aurora exascale supercomputer. Potential project areas include online training of robust AI/ML surrogates, AI driven workflows for efficient design space exploration and parameter optimization, cross-system workflows incorporating traditional HPC systems with novel AI accelerators, and developing performance benchmarks for evaluating hardware on current and future HPC systems.

In this role, you can expect to:

• Collaborate with scientists and researchers across multiple scientific domains and Argonne divisions, as well as other national labs and industry partners
• Contribute to open-source software used on platforms ranging from laptops to the world’s largest supercomputers
• Present research findings through journal publications, conference presentations, workshops, and other means
• Refine their skills and knowledge related to HPC and AI for science, including large scale distributed training, active learning and fine-tuning

Position Requirements

Required skills and qualifications:

• Ph.D. (completed within the last 0-5 years or soon-to-be-completed in 2024) in computer science, applied mathematics, physics, chemistry, or similar fields
• Experience contributing to scientific software in C++, Fortran, Python, or comparable languages
• Familiarity with building and deploying software on HPC systems
• Effective written and oral communication skills
• Ability to work individually and collaboratively as part of a team
• Ability to model Argonne’s core values: Impact, Safety, Respect, Integrity, and Teamwork

Preferred skills and qualifications:

• Demonstrated experience with parallel scientific computing (e.g., MPI, OpenMP, CUDA, etc.) or high-throughput computing on leadership class HPC systems
• Experience with machine learning methods and frameworks (e.g., TensorFlow, PyTorch, Jax, etc.), especially applied to scientific problems
• Experience with distributed ML training and inference tasks on multiple GPUs
• Experience with high-throughput computing or running large job ensembles on HPC systems

Job Family
Postdoctoral Family
Job Profile
Postdoctoral Appointee
Worker Type
Long-Term (Fixed Term)
Time Type
Full time
As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.
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• Collaborate with scientists and researchers across multiple scientific domains and Argonne divisions, as well as other national labs and industry partners
• Contribute to open-source software used on platforms ranging from laptops to the world’s largest supercomputers
• Present research findings through journal publications, conference presentations, workshops, and other means
• Refine their skills and knowledge related to HPC and AI for science, including large scale distributed training, active learning and fine-tunin