Postdoctoral Appointee - Synchrotron Studies of Crystal Defects for AI Modeling

Key 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.

Position Requirements

• Ph.D. completed in the past five years or soon-to-be completed in physics, materials science, chemistry, engineering, or a related discipline.
• Demonstrated 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.
• Able to work effectively in a collaborative, multi-institutional team environment.
• Able to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.
• Experience with in-situ or operando measurements under electrical or thermal bias.
• Familiarity with multimodal data correlation or integration with microscopy/spectroscopy datasets.
• Awareness of AI/ML data structures and metadata practices for interoperable experimental data.
• Strong background in materials physics, thin films, or functional oxides/2D materials.