Graduate Intern – AI-Driven Computational Synthesis of PGM-Free Fuel Cell Catalysts

Job overview

The Graduate Intern – AI-Driven Computational Synthesis of PGM-Free Fuel Cell Catalysts role is hybrid, primarily at the South Table Mountain campus with some work from home. The annual salary range is $44,500–$71,200. The position is with the Advance Computing Solutions group in the National Laboratory of the Rockies' Computational Science Center. The intern develops an agentic AI framework to automate machine-learned interatomic potential training and explore reaction energetics relevant to Fe-N-C fuel cell catalyst synthesis. The work combines AI, computational chemistry, and materials science to study synthesis conditions and generate chemical insight for the research team.

What you'll do

• Develop an agentic AI framework to automate machine-learned interatomic potential training and exploration of reaction energetics
• collaborate with researchers to study graphitization and iron incorporation into the nitrogen-carbon matrix for different precursors
• develop AI to process, analyze, and visualize simulation results
• author and present technical papers, reports, and conference proceedings.

What we're looking for

Skills & competencies

graduate intern

agentic ai

computational chemistry

fuel cell catalysts

fe-n-c

machine-learned potentials

materials science

hybrid

golden co

national laboratory of the rockies

$44,500–$71,200/year

Work arrangement

• Weekend coverage required

Benefits & perks

• Medical, dental and vision insurance, 403(b) savings plan with employer match, and sick leave where required by law
• eligibility rules apply.

Why this role

Hybrid graduate internship combining agentic AI, machine-learned interatomic potentials, and computational catalyst synthesis research.

About the employer

National Laboratory of the Rockies is hiring for this role. Industry: Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology). Sector: 54.