Assistant Physicist

Position Responsibilities

• Design, develop, and deploy AI/ML tools for x-ray imaging operations including reconstruction, super-resolution, spatiotemporal fusion, denoising, segmentation, and feature extraction — and integrate them into the beamline software stack.
• Build closed-loop experimental workflows in which AI agents use streaming data and real-time reconstruction and analysis to steer measurement decisions, and contribute to the development of a fully autonomous, AI-driven tomography beamline as a flagship project for the group.
• Collaborate with the APS Computation and AI (CAI) group and engage with other APS AI efforts and activities to align Imaging Group tools with facility-wide AI/ML infrastructure, data services, and computing resources, and to contribute to shared frameworks for autonomous experimentation.
• Develop automated pipelines for acquisition, quality control, and downstream analysis that translate beamline-scientist expertise and currently manual operational steps into robust, reusable software.
• Build and maintain pipelines for robust metadata capture and the systematic generation of curated, standardized datasets to support continual AI/ML model training and validation.
• Provide on-site support for user operations and data collection across the X-ray Imaging Group beamlines, working directly with beamline staff and users during experiments.
• Contribute to the longer-term extension of AI-enabled automation and autonomy across Imaging Group modalities, including micro- and nano-tomography and high-speed imaging.
• Prepare experiments and instruments for remote and AI-driven operation.

Position Requirements

• Ph.D. in computer science, electrical engineering, computational physics, computational materials science, applied mathematics, or a closely related field.
• Demonstrated expertise in AI/ML applied to imaging or scientific data, including hands-on experience developing and deploying deep-learning models (e.g., CNNs, vision transformers, diffusion models, or related architectures).
• Strong scientific software development skills in Python and modern deep-learning frameworks (e.g., PyTorch, TensorFlow), including experience with distributed training on high-performance computing resources.
• Experience with high-performance computing (HPC) and/or cloud environments.
• Experience with version control (e.g., Git) and collaborative software development practices.
• Experience working with experimental imaging data, ideally at a synchrotron, electron microscopy, medical imaging, or comparable facility.
• Ability to work effectively both independently and in a collaborative, team-based research environment.
• Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork.
• Interpersonal skills, oral and written communication skills, and ability to interact with people at all levels both within and outside the laboratory.