Lawrence Berkeley National Lab’s (LBNL) NERSC Division has an opening for a NESAP Machine Learning Postdoctoral Fellow to join the team.
In this exciting role, you will be a part of a multidisciplinary team composed of computational and domain scientists working together to develop machine learning approaches that run on the Perlmutter and future NERSC-10 system and produce mission-relevant science that pushes the limits of HPC. This position will carry out these efforts in collaboration with a project PI and team members, with the support of NERSC and vendor staff.
NESAP has established a track record of enabling its Postdocs to pursue careers in machine learning, data science, HPC, and scientific computing both in industry and at national labs.

DESIRED QUALIFICATIONS:

• Publication record or contributions to open source software projects commensurate with years of experience.
• Experience or interest in distributed training of complex deep learning models on large scientific datasets.
• Experience in keeping abreast with new deep learning innovations in training algorithms and neural network architectures.
• Experience with the development and performance optimization of scientific software in the HPC context.

• Work with domain experts and NERSC staff to develop, adapt, and optimize state-of-the-art AI models to solve scientific problems on HPC systems.
• Disseminate results of research activities through refereed publications, reports, and conference presentations. Ensure that new methods are documented for the broader community, NERSC staff, vendors, and NERSC users.
• Participate in Postdoctoral career and science enrichment activities within the Berkeley Lab Computing Sciences Area is encouraged.