Postdoc - AI-Accelerated Diffraction Imaging of Complex Materials
- Argonne National Laboratory
- Location: Lemont, IL
- Job Number: 7087681 (Ref #: ANL-411646)
- Posting Date: Oct 22, 2021
- Application Deadline: Open Until Filled
The Computational X-ray Science (CXS) group at the Advanced Photon Source (APS) (https://www.aps.anl.gov/) is involved in developing computational solutions for materials characterization using x-rays. CXS 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 and spectroscopy, as well as variants and combinations of these base techniques.
CXS is looking for a post-doctoral appointee to develop AI/ML techniques for automated data analysis of high energy x-ray tomographic data using both diffraction and absorption-based contrast. The successful candidate will work to accelerate processing and feature detection of this multi-modal 3D data, including use of automated morphology quantification. These computational developments are aimed at enabling studies of larger numbers of samples as well as more complex samples - which may contain multiple phases and several tomographic features – than possible 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.
Required Skills and Experience
- Ph.D. Degree and 0-1 years of experience OR
- Master’s Degree and 2-3 years of experience OR
- Bachelor’s Degree and 6-8 years of experience.
Desired Skills and Experience
- 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.
Questions about the posting should be directed to [email protected]
Job FamilyPostdoctoral Family
Job ProfilePostdoctoral Appointee
Worker TypeLong-Term (Fixed Term)
Time TypeFull time
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