Assistant Physicist

About this role

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 collaborating with facility-level computing, data, or AI groups to deploy software into production scientific environments.  

• Experience handling high-rate, large-volume imaging datasets and developing high-throughput reconstruction or analysis pipelines.  

• Experience contributing to open-source scientific software projects.  

• Familiarity with metadata standards, data management, and curation practices that support reproducible science and ML training datasets.  

• Familiarity with beamline data acquisition systems, detectors, or controls software, sufficient to integrate AI tools into operational workflows.  

Job Family Research Development (RD)

Job Profile Physics 2

Worker Type Regular

Time Type Full time

The expected hiring range for this position is $94,486.00 - $147,398.94.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, b

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