The Theory and Modeling Group at the Center for Nanoscale Materials (CNM) seeks an outstanding Assistant Scientist to lead and support frontier research at the intersection of AI/ML, data infrastructure, autonomous systems, and materials science. You will develop and apply advanced data-driven methodologies to accelerate discovery in materials design, characterization, and synthesis. The role combines self-directed and collaborative research aligned with CNM strategic themes, alongside scientific support for CNM users.
CNM is a DOE Office of Science user facility that provides researchers worldwide with world-class expertise and instrumentation for multidisciplinary nanoscience and nanotechnology. Learn more about CNM themes at: https://cnm.anl.gov
Focus Areas (expertise in one or more is highly desirable)
AI/ML for predictive modeling and inverse design of nanomaterials
Autonomous laboratories for materials synthesis and characterization
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
Interfacing AI tools with experimental facilities at CNM and Argonne
Key Responsibilities
Research leadership (50%)
Develop and lead an independent and collaborative research program in computational materials science aligned with CNM strategic themes and the DOE mission
Publish in refereed journals and present at conferences, symposia, and seminars
Contribute to proposal development and assist with execution and reporting for CNM, DOE, and other sponsors
User program engagement (50%)
Establish and maintain a vibrant, productive collaboration program with CNM users
Provide scientific and technical support for user computational projects to ensure successful execution and growth of user-led research
Computational and HPC support
Support end-users with HPC operations and maintenance issues, job optimization and scheduling, workflow understanding, and software installation
Collaboration and mentorship
Collaborate with internal and external researchers to drive innovation in nanoscience and nanotechnology
Contribute to CNM’s strategic scientific directions through pioneering R&D.
Provide work direction and mentorship to postdoctoral appointees, research assistants, students, and technical staff
Professional growth and operations
Work toward promotion from Assistant Scientist to Scientist
Manage vendor relationships as needed (hardware, cloud, managed support services)
Safety, security, and stewardship
Execute all activities in compliance with Argonne’s ES&H policies, Safeguards and Security policies, work rules, and safe practices
Position Requirements
Ph.D. in Materials Science, Physics, Chemistry, Chemical Engineering, Electrical Engineering, or a related field
Proven research track record in computational materials science and AI/ML, with applications in areas such as quantum information science, energy capture/storage/conversion, or microelectronics
Demonstrated ability to formulate scientific problems in the design and theory of nanoscale systems relevant to the DOE portfolio
Considerable skill in data management and high-performance computing, including workflow design and optimization
Strong oral and written communication skills, with the ability to work effectively with internal and external collaborators to achieve established goals
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
How to Apply Submit the following materials via the Argonne National Laboratory careers portal:
Cover letter detailing how your experience and expertise align with and will contribute to this position
Curriculum vitae with publication list and contact information for three professional references
2-page research statement outlining proposed research directions
1-page statement describing your approach to engaging and growing the CNM scientific user program
RD2: Bachelors and 5+ years of experience, Masters and 3+ years, or PhD and 0+ years, or equivalent
Job Family
Research Development (RD)Job Profile
Materials/Ceramics/Metallurgical 2Worker Type
RegularTime Type
Full timeThe expected hiring range for this position is $90,063.00 - $143,010.27.Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
Click here to view Argonne employee benefits!
As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.
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