The X-ray Imaging Group ( https://www.aps.anl.gov/Imaging ) of the X-ray Science Division (XSD) operates the full-field x-ray imaging beamlines at the Advanced Photon Source (APS) ( https://www.aps.anl.gov/ ) and pursues collaborative research across materials, energy, environmental, geo-, and life sciences using micro- and nano-tomography and high-speed imaging. With the APS Upgrade driving a substantial increase in data rates and experimental complexity, the group is investing in AI/ML-driven software, automation, and autonomous experimentation, including a planned fully autonomous, AI-driven tomography beamline - to keep pace with user demand and unlock new science. This work is carried out in close coordination with the APS Computational science and AI (CAI) ( https://cai.xray.aps.anl.gov/ ) group and other APS AI efforts and activities spanning data, computing, and machine learning across the facility. The appointee will benefit from access to world-leading experimental and computational resources at Argonne, including the upgraded APS and the exascale Aurora supercomputer. We seek highly motivated candidates with strong expertise in AI/ML and in the development of AI tools for scientific operations to join the X-ray Imaging Group. The successful candidate will lead the design and deployment of AI-powered software that supports user operations, automates data acquisition and analysis, and enables closed-loop, autonomous experiments across the group's beamlines. 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. + Present research results through publications, conferences, and scientific meetings. + May be required to perform other duties as assigned. **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. **Preferred Knowledge, Skills, and Experience** + Experience developing AI/ML methods specifically for x-ray imaging, tomography, or high-speed imaging applications. + Experience designing or contributing to automated, remote, or closed-loop ("self-driving") experimental workflows, including real-time data reduction, on-the-fly reconstruction, and AI-based experimental steering. + Experience collabor