Argonne

Scientific/Technical Lead for STEM Programs

Lemont, IL USA · Contract

Sponsorship not specified$70k-$109kDetected 50 days ago

PythonMachine LearningData AnalysisData ScienceData VisualizationLLMsAgentic AIAccessibilityProject ManagementResearchPublic Speaking

About the role

Argonne National Laboratory is a U.S. Department of Energy national laboratory conducting world-class research to address the nation's energy, environmental, and security challenges.
You will be responsible for designing and evolving the scientific challenge framework, leading facilitator training, and playing a key role in planning and implementing Argonne's local Jam event.
This hybrid position requires on-site presence a minimum of 2-3 days per week.

Design and develop scientific challenge frameworks that authentically integrate AI capabilities, domain science, and human judgment.
Develop and prototype challenge content including scientific storylines, curated datasets, and LLM workflows, iteratively testing across multiple AI platforms to ensure scientific integrity and pedagogical coherence.
Prepare and equip participating laboratory teams with the AI knowledge and challenge fluency needed to implement the Jam with fidelity across diverse lab environments.
Support the planning and implementation of Argonne's local Jam event, including presenting technical content and serving as a scientific and AI resource during the event.
Work in a matrixed environment, coordinating with curriculum developers, the Project Manager, and support teams across Argonne and other national laboratories.
Track and incorporate feedback from pilot testing, educators, and lab partners to iteratively improve Jam content and activities.

Bachelor's degree in a STEM field, artificial intelligence, computer science, engineering, data science, or a related technical discipline
Demonstrated experience working with LLMs in technical workflows, including prompt engineering, data analysis, agentic systems, and an understanding of model capabilities and limitations.
Strong scientific foundation with demonstrated ability to apply AI tools to scientific inquiry
experience in a specific STEM domain highly desired.
Demonstrated ability to track and interpret the rapidly evolving AI landscape, including emerging models, tools, and capabilities relevant to scientific applications.
Ability to communicate complex AI and scientific concepts clearly to diverse technical and non-technical audiences, including researchers, educators, and policymakers.
Experience working in a matrixed team environment.
Proficiency with relevant technical tools (e.g., Python, Jupyter notebooks, AI/ML platforms, data visualization tools).
Ability to model Argonne's Core Values: Impact, Safety, Respect, Integrity, and Teamwork.

This is a term position funded for 12 months, with potential for extension based on initiative success and future funding.
Travel to participating national laboratories and DOE events may be required.
advanced degree preferred but not required.

Identify and evaluate authentic scientific problems with the potential to illuminate key AI capabilities and limitations for non-expert audiences.
Design and develop scientific challenge frameworks that authentically integrate AI capabilities, domain science, and human judgment.
Develop and prototype challenge content including scientific storylines, curated datasets, and LLM workflows, iteratively testing across multiple AI platforms to ensure scientific integrity and pedagogical coherence.
Translate challenge frameworks into facilitator-ready resources that explicitly connect AI-enabled scientific inquiry to essential STEM workforce skills.
Prepare and equip participating laboratory teams with the AI knowledge and challenge fluency needed to implement the Jam with fidelity across diverse lab environments.
Support the planning and implementation of Argonne's local Jam event, including presenting technical content and serving as a scientific and AI resource during the event.
Please note that the pay range information is a general guideline only.

This listing is sourced directly from Argonne's careers page and normalized into a canonical job model.