Autonomous Laboratories, Robotics & Artificial Intelligence – Postdoctoral Researcher

LLNL•Livermore, CA

7d•Onsite

About The Position

We are seeking a highly motivated Postdoctoral Researcher to contribute to the design, development, and deployment of autonomous laboratories that accelerate scientific discovery through the integration of artificial intelligence, robotics, automation, data infrastructure, and experimental capabilities across advanced manufacturing, materials science, chemistry, and biology. This position offers a unique opportunity to work at the intersection of hands-on laboratory automation, robotics, and AI-enabled experimentation across a broad portfolio of application areas. This role is well suited for a researcher who is excited by both scientific investigation and platform development. You will help translate research questions into experimental workflows, prototype and troubleshoot automated and robotic systems, analyze data from active research campaigns, and contribute to the development of next-generation autonomous laboratories. This position is within the Materials Engineering Division (MED) in the Engineering Directorate.

Requirements

Ph.D. in Materials Science, Chemistry, Chemical Engineering, Mechanical Engineering, Electrical Engineering, Computer Science, Robotics, Physics, or a related field.
Experience performing research in materials science, chemistry, laboratory automation, robotics, AI/ML, or autonomous experimentation.
Ability to design, execute, analyze, and communicate scientific or engineering research.
Experience developing software for scientific computing, experimental control, data analysis, automation, or instrument integration.
Familiarity with one or more programming languages commonly used in research or automation environments, such as Python, MATLAB, LabVIEW, C/C++, or similar.
Ability to work hands-on with experimental systems, laboratory equipment, instruments, sensors, or robotic platforms.
Proficient verbal and written communication and interpersonal skills to collaborate effectively in a multidisciplinary team environment and present and explain technical information.
Ability to work independently while contributing effectively to collaborative research teams.

Nice To Haves

Experience developing or operating autonomous laboratories, self-driving labs, high-throughput experimentation platforms, or closed-loop experimental systems.
Experience integrating robotic systems, laboratory instruments, sensors, vision systems, synthesis or characterization tools, and other automated workcells.
Experience with instrument control, vendor APIs/SDKs, data acquisition, experiment orchestration software, laboratory information systems, or scientific data infrastructure.
Experience applying AI/ML methods to experimental science, such as Bayesian optimization, active learning, reinforcement learning, generative models, agent-based systems, computer vision, or predictive modeling.
Experience or interest in agentic AI, physical AI, embodied AI, vision-language-action models, or autonomous decision-making systems for planning, coordinating, and executing experiments on robotic, instrumented, or hardware-based laboratory platforms.
Experience with materials science, chemistry, advanced manufacturing, biology, or related experimental workflows, along with a demonstrated interest in developing autonomous discovery platforms for mission-relevant research.

Responsibilities

Design and validate autonomous experimental workflows for materials science, chemistry, advanced manufacturing, biology, or related scientific domains, transforming research questions and bench-scale procedures into reproducible automation protocols.
Integrate instruments, robotics, sensors, and software systems into coordinated autonomous or semi-autonomous laboratory platforms that enable safe, reliable, and scalable experimentation.
Develop software and data infrastructure in support of research campaigns for instrument control, data acquisition, experiment orchestration, workflow automation, metadata capture, traceability, and integration with laboratory information or data management systems.
Apply AI/ML methods to experimental discovery, including experiment planning, adaptive experimentation, predictive modeling, optimization, and analysis of experimental and instrument data.
Contribute to multidisciplinary research campaigns by troubleshooting platform performance, documenting and communicating results, publishing in peer-reviewed journals, presenting at conferences, and collaborating with scientists, engineers, roboticists, automation engineers, and AI/ML researchers.
Present research findings at seminars, conferences, and technical meetings; contribute to research design and project execution; collaborate in a multidisciplinary team environment; and publish results in peer-reviewed journals.
Perform other duties as assigned.