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The Advanced Photon Source (APS) ( https://www.aps.anl.gov/ ) at Argonne National Laboratory (Lemont, Illinois, US (near Chicago)) invites applicants for a postdoctoral position to develop and implement pioneering agentic AI workflows for autonomous materials characterization. We are building the next generation of AI-powered laboratories, where intelligent agents can formulate hypotheses, run simulations, design and conduct experiments, and analyze multimodal data streams in a continuous, real-time loop with minimal human intervention ( https://www.nature.com/articles/s41524-024-01423-2 , https://arxiv.org/abs/2509.00098 )

This project sits at the intersection of artificial intelligence and materials characterization and modeling. The goal is to create an AI system that can intelligently operate complex instruments and run simulations to accelerate discovery. This involves navigating vast parameter spaces, identifying rare or transient phenomena, and dramatically optimizing the use of precious beamtime at world-leading facilities.

The postdoctoral appointee will be responsible for developing the core components of this agentic system, which include designing agentic workflow for specific experiment tasks, implementing the infrastructure that handles message exchange and tool calls, and devising tools that control beamline instruments and launch simulations/analyses. You will help integrate the AI system with beamline control systems (e.g., EPICS) to close the autonomous loop. The position requires publishing results in high-impact journals, presenting at international conferences, and collaborating with a software engineering team to translate research into production-ready tools.

The successful candidate will be part of an inter-lab, highly inter-disciplinary team of experts in ML, applied math, HPC, signal processing, computational physics and materials science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of the world’s largest supercomputers (Polaris, Aurora) and some of the most advanced characterization tools in the world at Argonne and Sandia National Labs. Candidates with a background in deep learning, computational physics, computational materials science, inverse problems, signal processing, x-ray science etc. are encouraged to apply.

Position Requirements

+ PhD completed in the past 5 years or soon to be completed in a relevant field of study.

+ Knowledge of x-ray/optical/electron physics, including diffraction, optics, detectors, scattering etc.

+ Experience with deep learning (DL) libraries such as Tensorflow, PyTorch, JAX etc.

+ Experience with modern AI concepts such as large language models (LLMs), vision-language models (VLMs), model context protocol (MCPs), and the development of agentic AI tools.

+ Skill in programming languages such as Python, Go etc.

+ 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 scientific instrument control systems (e.g., EPICS).

+ Experience with developing LLM-based applications using Python APIs.

+ Experience with large scale molecular dynamics (MD) packages e.g. lammps

+ Experience with version control (e.g., Git) and collaborative software development practices.

+ Excellent written and oral communication skills.

+ Ability to work effectively as a member of a large, interdisciplinary team.

Job Family

Postdoctoral

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full time

The expected hiring range for this position is $70,758.00-$117,925.00.

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, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

Click here (https://www.anl.gov/hr/healthcare-insurance) to view Argonne employee benefits!

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