Senior Research Scientist, HPC and Al

Oak Ridge National Laboratory•Oak Ridge, TN

4d•Onsite

About The Position

The Analytics and AI Methods at Scale (AAIMS) group in the National Center for Computational Science (NCCS) is hiring a Research Scientist to advance the frontier of AI for science, including scientific reasoning, federated & collaborative learning, and reinforcement learning (RL) for self-improving models on leadership-class supercomputers. You’ll help design, train, and evaluate AI systems that plan, reason, and take actions to accelerate discovery across domains (materials, chemistry, climate, fusion, biology, and more). NCCS operates the Frontier exascale supercomputer and world-class data facilities. This role sits at the intersection of AI at scale and HPC, giving you access to unmatched resources to prototype new ideas, run experiments, and translate methods into scientific impact.

Requirements

Ph.D. in Computer Science, Computer Engineering, or a field closely related to the job duties of this position.
Demonstrated research in one or more areas of HPC or AI (e.g., large-scale training, scientific reasoning, reinforcement learning, or distributed systems).
Strong programming skills (Python, C/C++, or equivalent) and experience with ML frameworks (e.g., PyTorch).

Nice To Haves

Experience with large-scale experiments on HPC or cloud platforms.
Strong publication record commensurate with career stage.
Familiarity with distributed training frameworks (e.g., DeepSpeed, Megatron-LM, Ray).
Demonstrated ability to work collaboratively in multidisciplinary research teams.
Interest in developing open-source tools and contributing to community efforts.

Responsibilities

Conduct research in AI/ML at scale, working with cutting-edge HPC resources.
Collaborate with senior researchers and domain scientists on AI methods and scientific applications.
Contribute to peer-reviewed publications, technical reports, and proposals.
Engage in collaborative software development and open-source contributions.
Present research outcomes at conferences, workshops, and internal seminars.
Contribute to a supportive, inclusive, and collaborative team culture.