Postdoctoral Appointee - Accelerating AI for Science

Our MCS division is hiring a Postdoctoral Appointee to work on AI for Science.

AI is becoming pervasive in many science disciplines. As the understanding of how AI could contribute to science improves the size of the AI models and the volume of data needed to train these models increases. This growth of AI complexity brings several research opportunities concerning the scalability of AI training and the reduction of scientific data with AI.

The Postdoctoral Appointee will explore these two facets of AI for science. It will first explore asynchronous and multi-level techniques to improve AI data movements and reduce their overhead on execution. It will also explore AI based techniques to improve data reduction in particular for space efficient reduction of scientific data volumes.

Position Requirements

Required experience:
  • A recent or soon-to-be completed PhD degree, typically within 3 years
  • Ability to conduct interdisciplinary research at the intersection of HPC and deep learning
  • Participate in teamwork and broad collaborative efforts involving other laboratories and universities, supercomputer centers and industry
  • Scientific background at the intersection of HPC and AI and/or: experience with HPC platforms and parallel programming (CPUs, GPUs, NVMe, MPI, OpenMP, Cuda)
  • Experience with AI models and tools; data management in particular: data reduction (including compression), data storage and I/O best practices
  • Measuring and analyzing the performance impacts of software designs in distributed environments

Preferred experience:
  • Writing software that is portable to multiple HPC systems
  • Strong code development skills with C/C++ and Python and packaging tools such as spack

Job Family
Postdoctoral Family

Job Profile
Postdoctoral Appointee

Worker Type
Long-Term (Fixed Term)

Time Type
Full time

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