PSE Autonomous Discovery Scientist

Argonne National Laboratory

Lemont (IL)

On-site

USD 116,250 - 181,350

Full time

14 days+

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Benefits offered by this job

Comprehensive benefits
Support for independent research funding

Job summary

Argonne National Laboratory in Lemont, Illinois seeks a Scientist to drive cutting-edge research at the intersection of AI, autonomous platforms, and materials science. This role involves developing methodologies to accelerate discoveries in materials and chemistry.

Applicants should have a Ph.D. and a strong research background. The position includes responsibilities in program leadership, mentorship, and publication. Competitive salaries range from $116,250 to $215,280 annually, along with comprehensive benefits.

Qualifications

  • Proven research track record in materials science or chemistry using autonomous platforms and AI/ML.
  • Demonstrated ability to formulate scientific problems relevant to the DOE portfolio.
  • Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.

Responsibilities

  • Develop and lead an independent research program in materials science or chemistry using AI.
  • Publish in refereed journals and present at conferences.
  • Provide work direction and mentorship to postdoctoral appointees and students.

Skills

Expertise in materials or chemistry
Strong communication skills
Collaboration in multidisciplinary environments
Experience with AI/ML
Mentorship ability

Education

Ph.D. in Materials Science, Physics, Chemistry, or Computer Science

Job description

The Physical Sciences and Engineering Directorate seeks an outstanding Scientist to lead and support frontier research at the intersection of AI, autonomous platforms, data infrastructure, and materials science and/or chemistry. The candidate will have established expertise in materials or chemistry using autonomous platforms and AI to accelerate their research, with the expectation of forming an independently-funded research program within 2-3 years. The successful candidate will develop and apply advanced data-driven methodologies to accelerate discovery in materials/chemistry design, characterization, and synthesis.

Focus Areas
  • Autonomous laboratories for materials synthesis and characterization
  • 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
Key Responsibilities
  • Develop and lead an independent and collaborative research program in materials science or chemistry using AI and autonomous labs aligned with Argonne’s and the DOE’s missions.
  • Leverage existing facilities in autonomous labs, with the freedom to build other novel platforms.
  • Publish in refereed journals and present at conferences, symposia, and seminars.
  • Provide work direction and mentorship to postdoctoral appointees, research assistants, students, and technical staff.
  • 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, Computer Science, or a related field.
  • Proven research track record in materials science or chemistry using autonomous platforms and AI/ML.
  • 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 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.
Application Materials
  • 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.
  • 1-page research statement outlining proposed research directions.
Salary and Benefits
  • The expected hiring range for this position is $116,250 - $181,350 annually.
  • The expected hiring range for this position (alternative pay scale) is $138,000 - $215,280 annually.
  • The expected hiring range for this position (base range) is $116,250.00 - $181,350.00.
  • Pay will be determined based on scope, responsibilities, qualifications, business considerations, internal equity, and external market pay.
  • Comprehensive benefits are part of the total rewards package.
Job Family & Profile

Job Family: Research Development (RD)
Job Profile: Materials/Ceramics/Metallurgical 3
Worker Type: Regular Time – Full time

Equal Employment Opportunity

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 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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