Autonomous Infrastructure and Robotic Science Lead

About the Role

The Computing, Environment, and Life Sciences (CELS) Directorate seeks an outstanding scientist to lead and support frontier research at the intersection of AI, autonomous platforms, data infrastructure, and domain science. The candidate will lead Argonne’s Rapid Prototyping Laboratory (RPL), a team of computer scientists, roboticists, data scientists, and subject matter experts who develop hardware and software infrastructure for laboratory autonomy. RPL supports autonomous laboratories in domains including chemistry, biology, and quantum science, collaborates with domain scientists to execute autonomous experiments, and advances laboratory autonomy and robotics.

RPL develops the open-source Modular Autonomous Discovery for Science (MADSci) software framework for orchestrating autonomous laboratories, as well as software infrastructure supporting robotic workflows. The scientist will direct activities to advance these internal capabilities and foster collaborations across Argonne and beyond.

Focus Areas

Expertise in one or more of the following is highly desirable:

• Autonomous laboratories for chemistry, materials, biology, etc.
• AI/ML for predictive modeling and inverse design
• Generative models, reinforcement learning, and agent-based approaches to streamline experimentation and accelerate discovery
• Integration of HPC, data infrastructure, and ML pipelines for data-driven and autonomous research
• Digital twins and simulation-augmented AI tools

Responsibilities

• Evaluate the performance of assigned staff; recommend professional development, salary actions, and promotions
• Play a key role in the recruitment and selection of high-quality staff
• Report on research progress and new initiatives to division management, review committees, and funding agencies
• Provide supervisory oversight, including developing, motivating, and leading a team of professionals
• Guide the development of infrastructure for laboratory autonomy, including physical autonomous laboratories, robotics laboratories, and software frameworks for autonomous science and robotics
• Facilitate collaborations between RPL and teams at partner institutions developing autonomous science and robotics infrastructure
• Advance laboratory autonomy and robotics through RPL team efforts
• Publish in refereed journals and present at conferences, symposia, and seminars
• Provide work direction, supervisory oversight, and mentorship to postdoctoral appointees, research assistants, students, and professional technical staff
• Ensure all activities comply with Argonne’s ES&H policies, Safeguards and Security policies, work rules, and safe practices

About Argonne and the Rapid Prototyping Lab

Argonne National Laboratory is a U.S. Department of Energy multidisciplinary science and engineering research center tackling the largest scientific and engineering challenges of our time, from clean energy and advanced materials to artificial intelligence and quantum information science.

The Rapid Prototyping Lab (RPL), part of the Data Science and Learning division, develops integrated hardware and software solutions to accelerate scientific discovery through robotics and AI. RPL serves as a software and robotics hub where scientists collaborate, train the next-generation autonomous-discovery workforce, and develop open-source infrastructure for self-driving labs. Projects span new materials for energy storage, discovery of antimicrobial compounds, isotope production for medical applications, and more.

MADSci is RPL's flagship open-source software ecosystem and a core enabling technology for Argonne's broader Autonomous Discovery initiative, which aims to transform laboratory science by combining robotics, AI, and simulation to design, execute, and learn from experiments at unprecedented scale.

For more information:

• Rapid Prototyping Lab
• Autonomous Discovery at Argonne
• MADSci on GitHub
• AD-SDL organization on GitHub

Requirements

• Minimum of a Ph.D. in Computer Science, Materials Science, Physics, Chemistry, or a related field and 4+ years of experience, or equivalent
• Proven research track record in deploying automated and autonomous platforms and AI/ML to accelerate science
• Demonstrated ability to formulate scientific problems relevant to the DOE portfolio
• Strong oral and written communication skills, with the ability to work effectively with internal and external collaborators
• Demonstrated ability to collaborate in a multidisciplinary environment and provide scientific guidance to a diverse research community
• Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork
• Preferred experience leading and/or managing others from students to professional staff

Pay

The expected hiring range for this position is $148,125.00 - $231,075.00. Pay offered will be determined based on factors such as scope and responsibilities of the position, qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs.

Benefits

Comprehensive benefits are part of the total rewards package. View Argonne employee benefits.