Postdoctoral Position in Materials Sciences (Argonne National Laboratory)

Position Overview The Advanced Photon Source (APS) at Argonne National Laboratory 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. References: 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 includes navigating vast parameter spaces, identifying rare or transient phenomena, and dramatically optimizing the use of precious beamtime at world-leading facilities. Responsibilities The postdoctoral appointee will be responsible for: Developing the core components of the agentic system. Designing agentic workflows for specific experimental tasks. Implementing infrastructure that handles message exchange and tool calls. Creating tools that control beamline instruments and launch simulations/analyses. Integrating the AI system with beamline control systems (e.g., EPICS) to close the autonomous loop. Publishing results in high-impact journals. Presenting at international conferences. Collaborating with a software engineering team to develop production-ready tools. The appointee will work within a highly interdisciplinary team across ML, applied math, HPC, signal processing, computational physics, and materials science, with access to state-of-the-art resources including supercomputers (Polaris, Aurora) and advanced characterization tools at Argonne and Sandia National Labs. Required Qualifications 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 (diffraction, optics, detectors, scattering, etc.). Experience with deep learning libraries (TensorFlow, PyTorch, JAX, etc.). Experience with modern AI concepts such as LLMs, VLMs, MCPs, and development of agentic AI tools. Programming skills in Python, Go, etc. Ability to model Argonne’s core values: impact, safety, respect, integrity, teamwork. Strong interpersonal, oral, and written communication skills. Ability to work with individuals at all levels inside and outside the laboratory. Preferred Qualifications Experience with scientific instrument control systems (e.g., EPICS). Experience developing LLM-based applications using Python APIs. Experience with large-scale molecular dynamics packages (e.g., LAMMPS). Experience with version control (Git) and collaborative software development. Excellent written and oral communication. Ability to work effectively within a large, interdisciplinary team. Position Details Job Family: Postdoctoral Job Profile: Postdoctoral Appointee Worker Type: Long-Term (Fixed Term) Time Type: Full time Expected Hiring Range: $70,758.00 – $117,925.00 (Actual pay depends on qualifications, role scope, internal equity, and market conditions.) Comprehensive benefits are included. See Argonne employee benefits for details. Equal Employment Opportunity Statement Argonne National Laboratory is an equal employment opportunity employer. Argonne encourages applications from all qualified individuals and does not discriminate on any protected basis. Argonne employees and certain guest researchers/contractors are subject to restrictions related to participation in Foreign Government Sponsored or Affiliated Activities (DOE Order 486.1A). Disclosure during the application phase is required. All offers of employment are contingent upon: Background check (including criminal conviction history) Potential government access authorization requirements Failure to obtain or maintain required authorization may result in withdrawal of offer or termination of employment. Additional Information Interested in translating science into innovation? Build your career at Argonne. To learn more: Careers Programs and Benefits Argonne Science and Technology Reasonable accommodations or application support: careers@anl.gov or 630-252-2336 If you apply for this position please say you saw it on Engineeroxy

Position Overview

The Advanced Photon Source (APS) at Argonne National Laboratory 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.

References:
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 includes navigating vast parameter spaces, identifying rare or transient phenomena, and dramatically optimizing the use of precious beamtime at world-leading facilities.

Responsibilities

The postdoctoral appointee will be responsible for:

Developing the core components of the agentic system.
Designing agentic workflows for specific experimental tasks.
Implementing infrastructure that handles message exchange and tool calls.
Creating tools that control beamline instruments and launch simulations/analyses.
Integrating the AI system with beamline control systems (e.g., EPICS) to close the autonomous loop.
Publishing results in high-impact journals.
Presenting at international conferences.
Collaborating with a software engineering team to develop production-ready tools.

The appointee will work within a highly interdisciplinary team across ML, applied math, HPC, signal processing, computational physics, and materials science, with access to state-of-the-art resources including supercomputers (Polaris, Aurora) and advanced characterization tools at Argonne and Sandia National Labs.

Required Qualifications

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 (diffraction, optics, detectors, scattering, etc.).
Experience with deep learning libraries (TensorFlow, PyTorch, JAX, etc.).
Experience with modern AI concepts such as LLMs, VLMs, MCPs, and development of agentic AI tools.
Programming skills in Python, Go, etc.
Ability to model Argonne’s core values: impact, safety, respect, integrity, teamwork.
Strong interpersonal, oral, and written communication skills.
Ability to work with individuals at all levels inside and outside the laboratory.

Preferred Qualifications

Experience with scientific instrument control systems (e.g., EPICS).
Experience developing LLM-based applications using Python APIs.
Experience with large-scale molecular dynamics packages (e.g., LAMMPS).
Experience with version control (Git) and collaborative software development.
Excellent written and oral communication.
Ability to work effectively within a large, interdisciplinary team.

Position Details

Job Family: Postdoctoral
Job Profile: Postdoctoral Appointee
Worker Type: Long-Term (Fixed Term)
Time Type: Full time

Expected Hiring Range:
$70,758.00 – $117,925.00
(Actual pay depends on qualifications, role scope, internal equity, and market conditions.)

Comprehensive benefits are included.
See Argonne employee benefits for details.

Equal Employment Opportunity Statement

Argonne National Laboratory is an equal employment opportunity employer. Argonne encourages applications from all qualified individuals and does not discriminate on any protected basis.

Argonne employees and certain guest researchers/contractors are subject to restrictions related to participation in Foreign Government Sponsored or Affiliated Activities (DOE Order 486.1A). Disclosure during the application phase is required.

All offers of employment are contingent upon: