Argonne National Laboratory · 1 day ago
Staff Scientist - AI/ML and Autonomous Discovery for Nanomaterials (CNM)
Lemont, IL
Full-time
Onsite
Senior Level, Lead/Staff
$94K/yr - $147K/yr
5+ years expArgonne National Laboratory is seeking a staff scientist to lead and support cutting-edge research at the intersection of AI/ML, data infrastructure, autonomous lab systems, and nanomaterials science. The successful candidate will develop and apply advanced data-driven methodologies to accelerate discovery across materials design, experimental characterization, and synthesis, while providing support to CNM users.
EnergySecuritySocial Impact
No H1B
U.S. Citizen Only
Responsibilities
Develop and lead an independent and collaborative research program aligned with CNM strategic themes and the DOE mission (~50%). Publish results of independent and collaborative research in refereed journals and present at meetings, conferences, symposia, and seminars. Assist in the proper execution and reporting of projects for CNM, DOE, and other sponsoring sources
Establish and maintain a vibrant and productive collaborative program with CNM users (~50%). Provide scientific and technical support for user projects spanning modeling, autonomous synthesis, AI/ML, and experimental data interpretation, ensuring successful execution and dissemination of user-led research
Enable experimental–computational workflows by collaborating closely with experimental staff and users to integrate AI/ML and modeling with CNM characterization and synthesis capabilities (e.g., experiment planning, data reduction, automated analysis, multimodal data fusion, and in situ/operando interpretation)
Stay abreast of progress in relevant fields and contribute to CNM and the broader user community through method development, best practices, and mentoring
Support end-users with high performance computing and workflow needs (job optimization, workflow integration, data movement/management, software support) and with scalable analysis pipelines for experimental and simulation data
Collaborate with internal and external researchers to drive innovation and discoveries in nanoscience and nanotechnology
Contribute to the advancement of CNM strategic scientific directions through pioneering research and development
Provide work direction to postdoctoral appointees, research assistants, students, and technical staff working on projects within the candidate’s area of responsibility
Candidate may be required to manage vendor relationships as it pertains to hardware, cloud, and managed support services
Safety, Security, and Environmental Protection: All activities will be executed in compliance with ES&H and security responsibilities established by Argonne policies and safe practices
Qualification
Required
Ph.D. in Materials Science, Physics, Chemistry, Chemical Engineering, Electrical Engineering, or a related field
Proven track record of research in computational materials science and/or AI/ML, with demonstrated ability to collaborate effectively with experimental researchers and to impact experimentally driven programs
Demonstrated ability to formulate scientific problems relevant to nanoscale materials and DOE mission areas (e.g., microelectronics, energy capture/storage/conversion, quantum information science)
Experience with data-intensive research, scientific software, autonomous synthesis, reproducible workflows, and high-performance computing
Strong oral and written communication skills and the ability to work with internal and external contacts to achieve established goals
Strong ability to collaborate with a diverse research community and provide scientific guidance in a multidisciplinary environment
Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork
Preferred
5 years of experience as an independent researcher working in autonomous synthesis and/or AI for materials discovery
Benefits
Comprehensive benefits are part of the total rewards package
Company
Argonne National Laboratory
Argonne National Laboratory conducts researches in basic science, energy resources, and environmental management.
1001-5000 employees
Funding
Current Stage
Late StageTotal Funding
$41.4MKey Investors
Advanced Research Projects Agency for HealthUS Department of EnergyU.S. Department of Homeland Security
2024-11-14Grant· $21.7M
2023-09-27Grant
2023-01-17Grant
Leadership Team
Paul Kearns
Laboratory Director
Venkat Srinivasan
Director, Argonne Center for Collaborative Energy Storage Science (ACCESS)
Recent News
2026-01-25
Inside HPC & AI News | High-Performance Computing & Artificial Intelligence
2026-01-17
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