Postdoctoral Research Associate - AI for Science

Oak Ridge National Laboratory • Oak Ridge, TN

77d

About The Position

The Analytics and AI at Scale (AAIMS) group under Advanced Technology Section (ATS) of NCCS is hiring two postdoctoral research associates to push the frontier of agentic AI for science, scientific reasoning, federated & collaborative learning, and reinforcement learning (RL) for self-improving models, in the context of leadership scientific workflows and applications. You'll help design, train, and evaluate AI systems that plan, reason, and take actions to accelerate scientific 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 unmatched resources to prototype new ideas, run large ablations, and translate methods into scientific impact. We are an inclusive dynamic environment that welcomes those with initiative and creativity.

Requirements

• Ph.D. in Computer Science, Computer Engineering, a physical/computational science discipline (e.g., physics, chemistry, materials science, climate, biology), or a closely related field (earned within the last 5 years or expected before the start date).
• Demonstrated research in at least one: agentic AI/LLM agents, scientific reasoning or tool-augmented LLMs, RL (RLHF/RLAIF/online RL), or foundation models for science.
• Software engineering skills (Python) and experience with modern DL stacks (PyTorch) and multi-GPU training.
• Evidence of ability to conduct independent research and publish in peer-reviewed venues.

Nice To Haves

• Publications in leading venues (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR/ICCV/ECCV, ACL/EMNLP, MLSys/SC/HPDC).
• Hands-on with distributed training/inference (FSDP, DeepSpeed, Megatron-LM), accelerator programming, and large-scale data pipelines.
• Experience building agents that use tools/APIs (e.g., code interpreters, simulation frameworks, databases, lab instruments) and evaluation for long-horizon tasks.
• Experience with RL and post-training (reward modeling, preference learning, offline/online RL, self-play, curriculum learning, data selection).
• Experience with federated learning (cross-silo FL, FedAvg/FedProx/personalization), privacy-preserving methods (secure aggregation, differential privacy) and collaborative training/evaluation across heterogeneous data and compute.
• Background in one or more scientific domains (materials, chemistry, climate, fusion, biology) and/or scientific software ecosystems.
• Strong communication skills and a collaborative mindset in cross-disciplinary teams.

Responsibilities

• Conduct and publish original research on AI for science at scale on leadership-class systems.
• Design, implement, and benchmark large-scale training and post-training pipelines (including distributed data/compute and evaluation harnesses).
• Collaborate with domain scientists and external partners; co-develop end-to-end AI workflows that demonstrably accelerate scientific discovery.
• Architect and operate federated and collaborative learning experiments spanning multiple sites (national labs, universities, industry) with secure aggregation, heterogeneity-aware scheduling, robust and efficient training and fine tuning.
• Contribute to open-source software, datasets, and standardized evaluation suites; mentor interns and students.
• Communicate results through papers, artifacts, and presentations at top-tier venues.

Benefits

• Prescription Drug Plan
• Dental Plan
• Vision Plan
• 401(k) Retirement Plan
• Contributory Pension Plan
• Life Insurance
• Disability Benefits
• Generous Vacation and Holidays
• Parental Leave
• Legal Insurance with Identity Theft Protection
• Employee Assistance Plan
• Flexible Spending Accounts
• Health Savings Accounts
• Wellness Programs
• Educational Assistance
• Relocation Assistance
• Employee Discounts

What This Job Offers

• Career Level: Entry Level
• Industry: Professional, Scientific, and Technical Services
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees