Argonne National Laboratory
Postdoctoral Appointee - MSD AI for Materials Chemistry
Argonne National Laboratory, Lemont, Illinois, United States, 60439
Postdoctoral Appointee - MSD AI for Materials Chemistry
5 days ago Be among the first 25 applicants
The Materials Science Division is seeking applicants for a Postdoctoral Appointee who will conduct cutting‑edge research in AI for Materials Chemistry, with a focus on energy storage and conversion. This position offers an exciting opportunity to contribute to fundamental and applied research in materials chemistry using advanced computational techniques and artificial intelligence.
Project Involvement
Quantum Mechanical Calculations
Perform first‑principles or Density Functional Theory (DFT) calculations for molecules, materials, and interphases.
Utilize Molecular Dynamics (MD) simulations to study chemical transformations in materials.
Artificial Intelligence Applications
Leverage conventional machine learning techniques for materials property prediction and Bayesian approaches.
Explore Foundational Models and Agentic AI to address challenges in energy storage and conversion.
Position Requirements
Educational Background
A recent or soon‑to‑be‑completed Ph.D. (within the last 0‑5 years) in Materials Science, Computational Materials Science, Chemical Engineering, or a closely related field.
Technical Expertise
Comprehensive understanding of applied computational materials science, including electronic structure methods and molecular dynamics.
Experience with High‑Performance Computing (HPC) systems and intelligent workflows.
Programming Skills
Proficiency in C++ or Python programming languages is essential.
Research Contributions
Demonstrated publications in AI for Materials Chemistry.
Collaboration and Communication
Willingness to work on multiple projects and collaborate effectively with interdisciplinary teams.
Strong written and oral communication skills.
Core Values
Ability to model Argonne’s core values: impact, safety, respect, integrity, and teamwork.
Preferred Qualifications
Experience in integrating AI techniques with quantum mechanical calculations.
Familiarity with recent advancements in Foundational Models and Agentic AI.
Application Requirements
CV/Resume
Unofficial Ph.D. transcripts
If already awarded, a copy of your Ph.D. diploma (or proof of degree conferral by the position start date).
At the point of interview, candidates will be asked to submit the name/contact of three references.
Job Family Postdoctoral
Job Profile Postdoctoral Appointee
Worker Type Long‑Term (Fixed Term)
Time Type Full time
The expected hiring range for this position is $72,879.00–$121,465.00. This pay range is a general guideline only; the actual offer will be based on qualifications, role responsibilities, business considerations, and market comparisons. 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 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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The Materials Science Division is seeking applicants for a Postdoctoral Appointee who will conduct cutting‑edge research in AI for Materials Chemistry, with a focus on energy storage and conversion. This position offers an exciting opportunity to contribute to fundamental and applied research in materials chemistry using advanced computational techniques and artificial intelligence.
Project Involvement
Quantum Mechanical Calculations
Perform first‑principles or Density Functional Theory (DFT) calculations for molecules, materials, and interphases.
Utilize Molecular Dynamics (MD) simulations to study chemical transformations in materials.
Artificial Intelligence Applications
Leverage conventional machine learning techniques for materials property prediction and Bayesian approaches.
Explore Foundational Models and Agentic AI to address challenges in energy storage and conversion.
Position Requirements
Educational Background
A recent or soon‑to‑be‑completed Ph.D. (within the last 0‑5 years) in Materials Science, Computational Materials Science, Chemical Engineering, or a closely related field.
Technical Expertise
Comprehensive understanding of applied computational materials science, including electronic structure methods and molecular dynamics.
Experience with High‑Performance Computing (HPC) systems and intelligent workflows.
Programming Skills
Proficiency in C++ or Python programming languages is essential.
Research Contributions
Demonstrated publications in AI for Materials Chemistry.
Collaboration and Communication
Willingness to work on multiple projects and collaborate effectively with interdisciplinary teams.
Strong written and oral communication skills.
Core Values
Ability to model Argonne’s core values: impact, safety, respect, integrity, and teamwork.
Preferred Qualifications
Experience in integrating AI techniques with quantum mechanical calculations.
Familiarity with recent advancements in Foundational Models and Agentic AI.
Application Requirements
CV/Resume
Unofficial Ph.D. transcripts
If already awarded, a copy of your Ph.D. diploma (or proof of degree conferral by the position start date).
At the point of interview, candidates will be asked to submit the name/contact of three references.
Job Family Postdoctoral
Job Profile Postdoctoral Appointee
Worker Type Long‑Term (Fixed Term)
Time Type Full time
The expected hiring range for this position is $72,879.00–$121,465.00. This pay range is a general guideline only; the actual offer will be based on qualifications, role responsibilities, business considerations, and market comparisons. 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 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.
#J-18808-Ljbffr