Full-Time

Assistant Scientist

Data Driven and Autonomous Materials Discovery, Cnm

Posted on 5/30/2026

Argonne National Laboratory

Argonne National Laboratory

1,001-5,000 employees

Advanced scientific research and computing facilities

Compensation Overview

$90.1k - $143k/yr

Company Does Not Provide H1B Sponsorship

Woodridge, IL, USA

In Person

Category
AI & Machine Learning (2)
,
Required Skills
Machine Learning
Requirements
  • Ph.D. in Materials Science, Physics, Chemistry, Chemical Engineering, Electrical Engineering, or a related field
  • Proven research track record in computational materials science and AI/ML, with applications in areas such as quantum information science, energy capture/storage/conversion, or microelectronics
  • Demonstrated ability to formulate scientific problems in the design and theory of nanoscale systems relevant to the DOE portfolio
  • Considerable skill in data management and high-performance computing, including workflow design and optimization
  • Strong oral and written communication skills, with the ability to work effectively with internal and external collaborators to achieve established goals
  • Demonstrated ability to collaborate in a multidisciplinary environment and provide scientific guidance to a diverse research community
  • Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork
Responsibilities
  • Develop and lead an independent and collaborative research program in computational materials science aligned with CNM strategic themes and the DOE mission
  • Publish in refereed journals and present at conferences, symposia, and seminars
  • Contribute to proposal development and assist with execution and reporting for CNM, DOE, and other sponsors
  • Establish and maintain a vibrant, productive collaboration program with CNM users
  • Provide scientific and technical support for user computational projects to ensure successful execution and growth of user-led research
  • Support end-users with HPC operations and maintenance issues, job optimization and scheduling, workflow understanding, and software installation
  • Collaborate with internal and external researchers to drive innovation in nanoscience and nanotechnology
  • Contribute to CNM’s strategic scientific directions through pioneering R&D
  • Provide work direction and mentorship to postdoctoral appointees, research assistants, students, and technical staff
  • Work toward promotion from Assistant Scientist to Scientist
  • Manage vendor relationships as needed (hardware, cloud, managed support services)
  • Execute all activities in compliance with Argonne’s ES&H policies, Safeguards and Security policies, work rules, and safe practices
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

Simplify Jobs

Simplify's Take

What believers are saying

  • AI inference service monetizes spare supercomputer capacity for DOE researchers.
  • GridMind targets utility operators with explainable natural-language control-room support.
  • Polybot accelerated materials discovery from 4,300 combinations to 64 experiments.

What critics are saying

  • Federal appropriations pressure can defer facility upgrades and staffing.
  • Commercial AI and utility software vendors can outcompete research prototypes.
  • Accelerator procurement delays can slow AI capability upgrades and user access.

What makes Argonne National Laboratory unique

  • DOE multidisciplinary lab with >1,000 scientists and major user facilities.
  • Operates Advanced Photon Source and Argonne Leadership Computing Facility.
  • Combines industry, academia, and government collaborations on national challenges.

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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

1%

2 year growth

2%
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.

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。

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