Postdoc: AI‑Driven Synchrotron Defect Dynamics in Oxides

Argonne National Laboratory; Lemont (IL); On-site; USD 71,000 - 118,000; Full time

Job summary

Argonne National Laboratory is seeking two Postdoctoral Appointees in the Surface Scattering and Microdiffraction group to lead multimodal synchrotron studies of defects in oxides and 2D materials. You will design experiments and produce quantitative, AI-ready datasets linking structure, composition, and operating conditions to defect evolution.

You will collaborate across DOE facilities, integrating X-ray, electron microscopy, and spectroscopy datasets to uncover defect–property relationships

Qualifications

• Ph.D. completed in the past five years or soon-to-be completed in physics, materials science, chemistry, engineering, or a related discipline.
• Expertise in one or more synchrotron X-ray methods such as BCDI, XPCS, ptychography, Laue microdiffraction, or related coherent/imaging techniques.
• Proven ability to design, conduct, and analyze complex synchrotron experiments.
• Proficiency in scientific programming (Python, MATLAB, etc.) and quantitative data analysis.
• Excellent written and oral communication skills.
• Ability to work effectively in a collaborative, multi-institutional team environment.
• Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.
• Interpersonal skills and ability to interact with people at all levels both within and outside the laboratory.

Responsibilities

• Design and perform advanced synchrotron experiments to probe structural, chemical, and dynamic evolution of defects in thin films and heterostructures.
• Utilize techniques such as Bragg coherent diffraction imaging (BCDI), Laue microdiffraction, ptychographic laminography, and X-ray photon correlation spectroscopy (XPCS) to study strain, dislocation networks, voids, and interfacial morphology.
• Develop in-situ and operando experiments under electrical, thermal, or mechanical bias to capture real-time defect dynamics.
• Integrate multimodal datasets and collaborate with AI/ML teams for data fusion, physics-informed model validation, and causal discovery of defect–property relationships.
• Publish high-impact research results and present findings at national and international conferences.

Skills

Synchrotron techniques

Scientific programming

Experimental design

Collaborative teamwork

Technical communication

Education

PhD in physics, materials science, chemistry, or engineering

Tools

Python

MATLAB

Job description

Argonne National Laboratory is seeking two Postdoctoral Appointees in the Surface Scattering and Microdiffraction group to lead multimodal synchrotron studies of defects in oxides and 2D materials. You will design experiments and produce quantitative, AI-ready datasets linking structure, composition, and operating conditions to defect evolution.

You will collaborate across DOE facilities, integrating X-ray, electron microscopy, and spectroscopy datasets to uncover defect–property relationships