Argonne National Laboratory

Assistant Computational Chemist / Chemical Engineer - Catalysis

Argonne National Laboratory$94K — $147K *
Pharmaceuticals & Biotech
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Ph.D. in physical chemistry, inorganic chemistry, computational materials science, or chemical engineering with 3-6 years of postdoc experience
  • In-depth knowledge of quantum mechanics and catalysis principles
  • Significant experience in heterogeneous thermal catalysis and electrocatalysis with a focus on catalyst design and mechanistic studies
  • Strong computational skills in quantum mechanical methods for electronic structure and catalytic properties
  • Proficient in Python and relevant computational platforms
  • Experience implementing AI/ML methods for catalysis, especially in agentic workflows
  • Proven ability to write funding proposals and mentor junior researchers

Responsibilities

  • Perform computational studies on electrocatalysis and heterogeneous catalysis
  • Develop and apply multiscale modeling techniques for catalytic systems
  • Conduct spectroscopy simulations using XANES, EXAFS, and Mössbauer methods
  • Implement machine learning methods and automated workflows for catalysis simulations
  • Collaborate with experimental teams to analyze data and inform catalyst design
  • Contribute to research proposals and secure funding
  • Mentor postdoctoral researchers and graduate students

Benefits

  • Comprehensive benefits package including health, retirement, and professional development
  • Opportunities for interdisciplinary collaboration and research
  • Access to advanced lab facilities and computational resources
  • Engagement in cutting-edge research with real-world impact
  • Supportive work environment aligned with core values of safety, integrity, and teamwork
Full Job Description
The Chemical Sciences and Engineering Division at Argonne National Laboratory invites applications for a regular, full-time Assistant Computational Chemist / Chemical Engineer position. The successful candidate will lead and contribute to computational research in electrocatalysis and heterogeneous catalysis, working closely with experimental collaborators to advance fundamental understanding and catalyst design.

This role involves conducting multiscale modeling, spectroscopy simulations, and the development of machine learning methods and automated workflows for multi-fidelity, multiscale, and multiphysics simulations. The research will be closely integrated with corresponding experimental efforts.

Key Responsibilities
  • Perform computational studies in electrocatalysis and heterogeneous catalysis
  • Develop and apply multiscale modeling approaches to catalytic systems
  • Conduct spectroscopy simulations, including techniques such as XANES, EXAFS, and Mössbauer spectroscopy
  • Develop and implement machine learning methods and automated workflows for complex catalytic simulations
  • Collaborate closely with experimental researchers to interpret results and guide catalyst development
  • Contribute to proposal development and funding applications
  • Mentor postdoctoral researchers and graduate students


Position Requirements

  • Ph.D. in physical chemistry, inorganic chemistry, computational materials science, chemical engineering, or a related field, along with 3-6 years of postdoctoral research experience
  • Comprehensive understanding of quantum mechanics and catalysis
  • Extensive experience in heterogeneous thermal catalysis and electrocatalysis, including:
    • catalyst design
    • mechanistic studies
    • microkinetic modeling
    • reactor modeling
  • Strong computational expertise in applying quantum mechanical methods to determine electronic structure, catalytic properties, and reaction mechanisms
  • Demonstrated experience in spectroscopy simulations, including XANES, EXAFS, and Mössbauer spectroscopy
  • Proficiency in Python and relevant computational platforms
  • At least 1-2 years of experience adapting and implementing AI/ML methods in catalysis, including:
    • machine learning interatomic potentials
    • agentic workflows
  • Experience in proposal writing and funding applications
  • Experience mentoring postdoctoral researchers and graduate students
  • Excellent written and oral communication skills
  • Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork


Preferred Qualifications
  • Experience with PGM-free oxygen reduction reaction (ORR) catalysts
  • Experience with CO₂ reduction catalysis


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
Chemistry 2

Worker Type
Regular

Time Type
Full time

The expected hiring range for this position is $94,486.00 - $147,398.94.

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!

About Argonne National Laboratory

Argonne National Laboratory is a science and engineering research national laboratory operated by the University of Chicago Argonne LLC for the United States Department of Energy. It is located in Lemont, Illinois, outside of Chicago. Argonne conducts research in a variety of fields, including energy, environment, national security, and technology. The laboratory was founded in 1946 as part of the Manhattan Project and has since become one of the largest science and engineering research laboratories in the United States.
Learn more about Argonne National Laboratory
Size
3,400 employees
Industry
Founded
1946

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