Postdoctoral Appointee - AI for Synchrotron Imaging

Argonne National Laboratory; Lemont (IL); On-site; USD 72,879 - 121,465; Full time

Benefits offered by this job

Comprehensive benefits

Job summary

Argonne National Laboratory is seeking a Postdoctoral Appointee for the Computational Science and Artificial Intelligence Group. This position focuses on developing learning-enabled imaging techniques to advance research in soil microbial communities.

Applicants should hold a Ph.D. and possess strong skills in machine learning, computational imaging, and scientific programming. The role offers a full-time contract with a competitive salary range of $72,879 to $121,465, along with comprehensive benefits.

Qualifications

• Ph.D. completed in the past 5 years or soon-to-be completed.
• Strong expertise in machine learning, computational imaging, computer vision, or signal processing.
• Proficiency in scientific programming and ability to implement research-grade algorithms.

Responsibilities

• Develop learning-enabled algorithms for 3D reconstruction.
• Implement adaptive acquisition strategies to improve image quality.
• Advance multimodal analysis methods to construct coherent models.

Skills

Machine learning

Computational imaging

Computer vision

Signal processing

Scientific programming

Interdisciplinary collaboration

Education

Ph.D. in Electrical Engineering, Computer Science, Applied Mathematics, Physics, or related field

Tools

Modern ML frameworks

Job description

Position Overview

We are seeking a Postdoctoral Appointee to join the Computational Science and Artificial Intelligence Group in the X-ray Science Division of the Advanced Photon Source (APS) at Argonne National Laboratory to advance learning‑enabled imaging methods. This position offers a unique opportunity for candidates with backgrounds in electrical engineering, computer science, applied mathematics, or physics to apply their expertise to challenging problems in computational imaging, while collaborating with leading experts in physics, biology, and environmental science.

Research Context: Soil microbial communities play a fundamental role in carbon and nutrient cycling, yet their spatial organization and interactions have remained difficult to study because of the opacity and complexity of soil. The APS at Argonne National Laboratory is a world‑leading synchrotron facility recently upgraded to deliver nanometer‑to‑micron resolution imaging with dramatically increased X‑ray flux. This makes it possible to visualize the interplay of soil structure and microbial life at scales bridging nanometers to millimeters, creating a unique opportunity to investigate how microbial communities are organized and interact within their natural environments.

Your Role

Responsibilities include:

• Develop learning‑enabled algorithms for 3D reconstruction of noisy and heterogeneous synchrotron datasets.
• Implement adaptive acquisition strategies that guide beamline measurements in real time to increase efficiency and improve image quality.
• Advance multimodal analysis methods that align and fuse structural, chemical, and biological signals to construct coherent models of microbial organization across scales.

May be required to perform other duties as assigned.

Position Requirements

• Ph.D. completed in the past 5 years or soon‑to‑be completed in Electrical Engineering, Computer Science, Applied Mathematics, Physics, or a related field.
• Strong expertise in machine learning, computational imaging, computer vision, or signal processing.
• Proficiency in scientific programming and modern ML frameworks, with the ability to implement and debug research‑grade algorithms.
• Demonstrated ability to work on complex data analysis problems and deliver robust computational solutions.
• Excellent communication skills and a strong interest in interdisciplinary collaboration.
• 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 with synchrotron or tomographic imaging datasets.
• Background in inverse problems or physics‑informed machine learning.
• Exposure to scientific imaging applications (for example, biological, environmental, or materials science).

Job Family

Postdoctoral – Worker Type: Long‑Term (Fixed Term). Time Type: Full time.

The expected hiring range for this position is $72,879.00–$121,465.00. Additionally, comprehensive benefits are part of the total rewards package.

As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation.