Full-Time

Assistant Beamline Scientist

CNM-APS Hard X-Ray Nanoprobe

Updated on 7/21/2026

Argonne National Laboratory

Argonne National Laboratory

1,001-5,000 employees

Advanced scientific research and computing facilities

Compensation Overview

$94.5k - $147.4k/yr

Company Does Not Provide H1B Sponsorship

Woodridge, IL, USA

In Person

Category
AI & Machine Learning (1)

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Requirements
  • A Ph.D. in physics, materials science, chemistry, engineering, or a related physical science discipline
  • A strong background in experimental or analytical synchrotron X-ray research and/or other advanced microscopy techniques relevant to materials research
  • Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork
Responsibilities
  • Develop and lead an independent, high-impact research program in synchrotron X-ray microscopy and related nanoscale characterization methods
  • Leverage the capabilities of the APS Upgrade and CNM/APS HXN beamline to pursue innovative scientific opportunities
  • Conduct research aligned with CNM strategic priorities in nanoscale materials and device science
  • Support and guide user experiments at the beamline, helping enable successful and cutting-edge research outcomes
  • Advance beamline capabilities through new instrumentation, experimental methods, and analytical approaches
  • Collaborate with staff, users, and external partners across a broad range of disciplines
  • Contribute to the growth and scientific vitality of the CNM user program
Desired Qualifications
  • Laser or electrical pump-probe methods
  • Coherent diffraction imaging and phase retrieval
  • Artificial intelligence and machine learning for experimentation or data analysis
Argonne National Laboratory

Argonne National Laboratory

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Argonne National Laboratory advances scientific discovery and sustainability by providing access to large-scale research facilities and high-performance computing for government, academia, and industry partners. Researchers use the Advanced Photon Source for atomic-level materials studies and the Argonne Leadership Computing Facility for complex simulations and data analysis. The lab differentiates itself through its shared-use, multi-institution partnerships and a focus on eco-innovation, net-zero goals, and AI accelerator development. Its aim is to address real-world energy, materials, and data science challenges by combining cutting-edge infrastructure with collaborative research efforts.

Company Size

1,001-5,000

Company Stage

Grant

Total Funding

$19.7M

Headquarters

Lemont, Illinois

Founded

1946

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Simplify's Take

What believers are saying

  • DOE secured $37 million for AI for Science, enabling virtual X-ray and microscopy environments across five labs.
  • Solstice and Equinox systems will deploy 110,000 NVIDIA Blackwell GPUs, creating the largest AI supercomputer in the DOE complex.
  • Chain Reaction Innovations incubator selected five clean energy startups in 2026 to scale scientific discoveries into businesses.

What critics are saying

  • DOE budget reallocation to Genesis Mission reduces ANL's standalone AI accelerator funding within 6–12 months.
  • SambaNova SN40L supply chain fragility threatens Metis cluster scalability and inference service uptime in 9–15 months.
  • Open-source ChemGraph allows private rivals to replicate AI-computational chemistry workflows without facility access.

What makes Argonne National Laboratory unique

  • Argonne operates the Aurora exascale supercomputer, ranked No. 1 in AI benchmarks for drug discovery.
  • The lab offers unique AI inference services on spare GPU capacity from Sophia and Metis clusters.
  • Argonne leads autonomous discovery with Polybot, an AI-guided robotic lab reducing material experiments from 4,300 to 64.

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Benefits

Health Insurance

Dental Insurance

Vision Insurance

Life Insurance

Disability Insurance

Paid Vacation

Paid Sick Leave

Paid Holidays

Remote Work Options

Flexible Work Hours

401(k) Retirement Plan

401(k) Company Match

Professional Development Budget

Wellness Program

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

1%
Business Wire
Mar 26th, 2026
Argonne Lab develops GridMind AI agent to support power grid operators

Researchers at the US Department of Energy's Argonne National Laboratory have developed GridMind, an agentic AI system designed to assist power grid operators through natural language interaction. The system functions as a reasoning co-pilot for control rooms, simplifying complex grid management tasks. GridMind employs a multi-agent architecture where specialised AI agents handle different functions, such as power scheduling and weather-based contingency planning. Large language models coordinate these agents to analyse situations, reason across different tasks and provide explainable recommendations. The system transforms technical analysis into conversational support whilst maintaining rigorous accuracy. Tests on standard power grid models demonstrated that GridMind consistently produced correct results across multiple state-of-the-art language models. The technology aims to accelerate decision-making by integrating disconnected workflows into a coherent reasoning engine.

Yahoo Finance
Mar 11th, 2026
AI adviser helps Argonne's robotic lab discover advanced electronic materials in just 64 experiments

A research team led by the US Department of Energy's Argonne National Laboratory has developed an AI adviser that optimises machine learning algorithms during autonomous experiments, accelerating discovery of advanced electronic materials. The system was applied to Polybot, Argonne's AI-guided robotic laboratory, to investigate mixed ion-electron conducting polymers for wearable electronics and energy storage. The adviser evaluates algorithm performance in real time and communicates insights to scientists who refine experimental plans. It reduced the study to just 64 experiments from over 4,300 possible combinations. During testing, the adviser suggested switching AI algorithms, leading to significant performance improvements, and identified deposition speed as a key performance driver. The research was published in Nature Chemical Engineering and included collaborators from the University of Chicago, Lawrence Berkeley National Laboratory and other institutions.

Argonne National Laboratory
Jun 2nd, 2022
5 clean energy startups chosen for Argonne’s Chain Reaction Innovations - Chain Reaction Innovations

An energy and science incubator for transformative technologies

Techable
Nov 21st, 2020
アルゴンヌ国立研究所、1万個以上のセンサーを使って交通状況を瞬時に予測!

米国エネルギー省(DOE)のアルゴンヌ国立研究所の研究者らは、ローレンスバークレー国立研究所が主導するモビリティシステムの設計・計画に関するプロジェクトの一環として、交通状況を予測するAIシステムを開発中だ。