Postdoctoral Appointee in- Developing High-Energy Diffraction Microscopy to Investigate Battery Materials

Argonne National Laboratory X-ray Science Division

The X-ray Science Division (XSD) at the Advanced Photon Source (APS) ( is involved in developing computational solutions for materials characterization using high-energy x-ray diffraction microscopy (HEDM).

XSD supports a wide variety of advanced scientific instruments at the APS by developing new algorithms, AI/ML models and building software frameworks for x-ray techniques of diffraction imaging, as well as variants and combinations of these base techniques.

This project is looking for a postdoctoral appointee to develop AI/ML techniques for automated data analysis of high-energy x-ray diffraction microscopy data.

The successful candidate will work to accelerate processing and feature detection of this 3D data, including use of automated morphology quantification.

These computational developments are aimed at enabling studies of larger numbers of grains associated with battery materials as an example complex samples - which may contain multiple phases and more extreme forms of strain than typically encountered today.

Candidates with a background in machine learning, computational materials science, computational physics, image processing, inverse problems, applied math and x-ray science are encouraged to apply.

Questions about the posting should be directed to and

Position Requirements

PhD obtained within the last 3 years. Experience in developing AI/ML models applied to Materials Science or Physics problems.

Knowledge of computation tools for development of software including programming languages such as Python. Skill with machine learning frameworks including scikit-learn, Tensorflow and PyTorch.

Knowledge of diffraction, crystallography and microtomography Ability to work in a team environment. Good written and communication skills.

Job Family Postdoctoral Family Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time

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