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Oak Ridge National Laboratory · 4 hours ago

R&D Associate Staff - Atomic manipulation with AI agents

Oak Ridge, TN

Full-time

Onsite

Senior Level, Lead/Staff

2+ years exp

Oak Ridge National Laboratory is seeking a Research & Development Associate Staff Scientist to support research in developing novel AI agents for atomic scale microscopy platforms. The role involves designing AI frameworks for atomic manipulation and integrating simulations with AI to drive materials discovery.

Advanced MaterialsClean EnergyEnergyEnergy ManagementManufacturingNuclearRenewable Energy

No H1B

U.S. Citizen Only

Responsibilities

Design, implement, and deploy advanced agent-based AI frameworks (e.g., reinforcement learning, hierarchical policies, multimodal agents) and apply them to scanning probe microscopy platforms—including STM and STEM—to autonomously manipulate atoms and construct designer lattices with targeted quantum or electronic properties

Extend AI-driven control approaches to thin-film synthesis platforms, such as pulsed laser deposition (PLD), by developing closed-loop optimization strategies for growth conditions, defect engineering, and in-situ diagnostics

Integrate simulations, theory, and experiment by developing workflows that combine atomistic modeling, surrogate models, and agent policies to guide experimental decision-making for materials discovery

Develop robust automation pipelines that orchestrate data acquisition, analysis, experimental control, and model retraining, enabling reproducible, scalable, and high-reliability AI-driven experimentation

Report and publish scientific results in peer-reviewed journals in a timely manner

Present results at international scientific conferences and meetings

Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success

Qualification

PhD in relevant fieldMachine learning methodsMicroscopy platform experienceReinforcement learningPulsed laser depositionOpen-source AI/ML packagesSolid-state physicsCommunication skillsCollaborative teamworkSelf-starter

Required

A PhD in Physics, Materials Science, Chemistry, Computer Science, or closely related field

Sound understanding of advanced ML concepts and architectures and hands-on experience with open-source AI/ML packages (such as PyTorch, scikit-learn, TensorFlow, JAX etc.)

Two or more years of experience in applying machine learning methods for instrument control, such as on a microscope, or on a nanomaterials synthesis platform resulting in publishable scientific results

Two or more years of experience with state-of-the-art machine learning methods such as reinforcement learning and Bayesian optimization

Experience with operating microscopy platforms (scanning probe or electron microscopy) and/or nanomaterial synthesis platforms (such as physical vapor deposition or molecular beam epitaxy)

Preferred

Strong understanding of concepts in solid-state physics, ferroelectrics and/or 2D materials

Experience with advanced AI/ML methodologies relevant to autonomous science, such as generative models, causal inference, symbolic regression, or model-based RL for scientific reasoning and materials design

An excellent record of productive and creative research shown by a record of publications in peer-reviewed journals

Demonstrated coding abilities and a commitment to open science as shown through code repositories (e.g., GitHub)

Excellent written and oral communication skills

Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory

Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to changing needs