Postdoctoral Appointee – Battery Modeling, Electrochemistry, and AI

We invite applications for a Postdoctoral Appointee position in the Chemical Sciences and Engineering Division (CSE) at Argonne National Laboratory.

Working under the guidance of a supervisor, the successful candidate will conduct research focused on meso- and macroscale mathematical modeling of next-generation batteries, while leveraging advanced artificial intelligence (AI) tools to accelerate scientific discovery. Research areas include solid-state batteries with lithium and sodium metal anodes, as well as the morphology evolution of materials coupled with electrochemical and mechanical phenomena.

The selected candidate will develop computational models at the mesoscale and/or macroscale based on the principles of mass, momentum, and energy conservation to describe processes such as morphological change, dendrite growth, side reactions, delamination, and related behavior in hard and soft materials. A strong emphasis will be placed on the integration of AI methods and agentic workflows into model development and scientific analysis.

This position offers the opportunity to collaborate closely with experimental teams working in areas such as electrochemical characterization and synchrotron analysis, as well as with theoretical researchers specializing in atomistic simulation, density functional theory (DFT), and ab initio molecular dynamics (AIMD). The successful candidate will also engage with collaborators across Argonne, other national laboratories, universities, and international research institutions.

Key Responsibilities

• Develop mesoscale and/or macroscale computational models for battery materials and processes

• Implement models and perform numerical simulations

• Analyze and interpret simulation and experimental data

• Integrate AI tools and workflows to enhance modeling and accelerate learning

• Collaborate with interdisciplinary experimental and theoretical research teams

• Prepare manuscripts for submission to peer-reviewed journals

• Present research findings at scientific conferences and meetings

• Prepare reports, presentations, and technical summaries for group meetings and sponsor reporting requirements

Position Requirements

• Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Chemical Engineering, Mechanical Engineering, Materials Science, Chemistry, or a related field

• A deep understanding of electrochemistry, electrochemical engineering, and battery science

• Strong experience in developing computational models based on mass, momentum, and energy balance principles

• Strong skills in applying AI tools and agentic workflows to scientific research

• Some experience in proposing, planning, and designing experiments

• Demonstrated ability to process, analyze, and interpret research results

• Strong skill in formulating and solving scientific problems

• Excellent written and oral communication skills

• Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork

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.

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.

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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.