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Postdoctoral Appointee – Battery Manufacturing Research
Job in
Northern, Floyd County, Kentucky, USA
Listed on 2026-08-13
Listing for:
RFCSR
Full Time
position Listed on 2026-08-13
Job specializations:
-
Research/Development
Research Scientist -
Engineering
Research Scientist
Job Description & How to Apply Below
Postdoctoral Appointee – Battery Manufacturing Research
Salary Range: $70,758 – $117,925/year Application Review:
Ongoing #: 420843
The Applied Materials Division (AMD) at Argonne National Laboratory is seeking a Postdoctoral Appointee to join a high-impact team working at the frontier of next-generation battery research . This role focuses on the design, scale-up, and manufacturing of advanced cathode materials for lithium-ion and sodium-ion batteries , in close collaboration with national labs, industry, and academic partners.
Research Focus
- Development of scalable synthesis routes for advanced battery materials
- Process optimization for cost-effective, high-performance cathode production
- Electrochemical evaluation, full-cell prototyping, and technology transfer
- Collaborative use of synchrotron X-ray ,
electron microscopy , and interface analysis
Facility Advantage Work at the Materials Engineering Research Facility (MERF) — a pre-pilot-scale R&D facility for process development and prototyping in battery technologies.
Minimum Qualifications
- Ph.D. (within past 0–5 years) in Materials Science ,
Chemical/Mechanical Engineering ,
Chemistry , or Condensed Matter Physics - Strong hands-on experience with cathode material synthesis and electrochemical characterization
- Familiarity with X-ray diffraction , structural analysis, and multiscale materials characterization
- Proven track record through publications, patents, or presentations
- Excellent verbal and written communication skills
- Demonstrated ability to work in multidisciplinary teams
Preferred Qualifications
- Experience with synchrotron X-ray ,
neutron , or electron microscopy techniques - Skilled in impedance spectroscopy and operando characterization
- Background in crystallography ,
machine learning for materials , or spectral data analysis
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