aimlroles

Postdoctoral Appointee - AI/ML for Particle Accelerators

ARGONNE Open · verified Oct 22, 2026
Lemont Full-time Mid-level AI Research

At a glance

Mid-level AI Research role at ARGONNE. Lemont · full-time · $72,879–$121,465 base.

SalaryStated by ARGONNE
$72,879 – $121,465
Base salary for this role, in USD per year, as published in the posting.
RoleAI Research
SeniorityMid-level
LocationLemont
EmploymentFull-time
Base pay$72,879–$121,465
PostedJul 22, 2026 · 3mo ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build and deploy AI/ML methods to analyze, tune and control particle beams and accelerator systems
  • Explore agentic AI and language-model applications for system analysis, operator decisions and complex workflow automation
  • Test methods on the APS injector and upgraded storage ring, assessing their value for accelerator operations
  • Apply adaptive approaches to machine tuning, diagnostics and fault response

What you bring

  • A PhD completed within the past five years, or nearing completion, in accelerator physics or a related field
  • Strong programming ability, including proficiency in Python and working knowledge of UNIX or Linux
  • PhD training in physical sciences, mathematics, computer science or electrical engineering is also considered with an interest in accelerator physics

Who this fits

This is a multi-year, full-time postdoctoral appointment centered on hands-on accelerator experiments and AI/ML research. It suits a recent or soon-to-finish doctoral researcher interested in accelerator physics; relevant machine-learning or accelerator-operation experience is preferred.

From the employer

Postdoctoral Researcher in artificial intelligence and machine learning (AI/ML) for advanced tuning and diagnosis of particle accelerators.

The Accelerator Operations and Physics (AOP) Group of the Accelerator Systems Division (ASD), Advanced Photon Source (APS) is hiring a postdoctoral researcher for a multi-year appointment.

The postdoctoral researcher will work to develop and deploy advanced AI/ML methods for analysis, tuning, and control of particle beams and accelerator systems, with applications to the APS injector and the newly-upgraded APS storage ring. This work will explore applications of LLMs to accelerators, specifically, use of agentic AI to support intelligent system analysis, aid operator decision-making, automate complex workflows, and enable more adaptive approaches to machine tuning, diagnostics, and fault response. Experimental work on the existing APS injector accelerator complex and the new APS storage ring will be done to test the methods and assess their usefulness for accelerator operation.

Position Requirements

  • PhD completed in the past 5 years or soon-to-be completed in accelerator physics or a related field is strongly preferred. PhD graduates in other branches of physical sciences, or in math, computer science, and electric engineering who have an interest in accelerator physics will also be considered.

  • Strong programming skills.

  • Proficiency in the Python programming language.

  • Working knowledge of UNIX or Linux.

Preferred Knowledge, Skills, and Experience

  • Experience with machine learning and accelerator operation.

  • Experience working with complex algorithms.

  • Experience using computing clusters for simulation and data analysis.

  • Experience with accelerator modeling and simulation codes, such as Elegant and Cheetah.

  • Experience with SDDS, Tcl/Tk, and scripting in Linux environment.

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 $72,879.00-$121,465.00.

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.

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