Argonne National Laboratory
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Postdoctoral Appointee-AI Architectures for Science

Position Description

The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by providing supercomputing resources and expertise to the research community. ALCF computing resources—available to researchers from academia, industry, and government agencies—support large-scale, computationally intensive projects aimed at solving some of the world’s most complex and challenging scientific problems.

The ALCF has an opening for a postdoctoral position on evaluating the efficacy of AI architectures for scientific machine learning and on the design of next generation AI architectures for science. In particular, the ALCF is exploring using novel AI hardware working in collaboration with vendors, including Cerebras, Sambanova, Groq, Nvidia, Intel, among others, for scientific machine learning. We are work with a diverse set of science applications, including but not limited to: Computational Chemistry, Plasma Physics, High Energy Physics, analysis of Light Source data such as that from the Advanced Photon Source, Biology, Astronomy, and other science disciplines. The successful candidate will be expected to implement, optimize and scale machine learning models on cutting edge AI hardware and systems to fully exploit the architectural and software features these systems. The candidate will also work on research and development on how to integrate and scale AI architectures with existing and upcoming supercomputers at the facility to accelerate science insights.

Position Requirements

Recent PhD (within 3 years) in a physical science, computer science, or engineering or related field.
Comprehensive experience programming in one or more programming languages such as C, C++, and Python
Experience in profiling and performance analysis.
Experience with machine learning methods and deep learning frameworks, including Tensorflow and PyTorch is desirable
Experience in heterogenous programming, including GPU programming, compilers and parallel programming is valuable.
Ability to create, maintain, and support high-quality software is essential. The successful candidate will be expected to work with and contribute to domain-specific software and models.
Good communications skills and previous experience in writing technical papers and presentations at national and international symposia is expected.
Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.