Graduate Intern - Agentic AI-Driven Computational Synthesis of PGM-free Fuel Cell Catalysts

Graduate Intern – Agentic AI-Driven Computational Synthesis of PGM-free Fuel Cell Catalysts Location: CO - Golden • Position Type: Intern (Fixed Term) • Hours Per Week: 40 About NLR Working at NLR NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development. Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth. At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being. Job Description The Advance Computing Solutions group in the NLR Computational Science Center has an opening for a graduate intern in computational synthesis, with a particular emphasis on development and utilization of an agentic AI framework that automates the exploration of relevant reaction energetics using machine-learned interatomic potentials (MLIPs). The researcher will work with an interdisciplinary team to develop agentic AI that automates the training of MLIPs of desirable accuracy and uses the trained MLIPs to discern the effect of varying different reaction conditions on the final synthesized Fe‑N‑C fuel cel catalyst. We are looking for a dynamic, motivated researcher with a strong technical background and an interest in the mission of NLR. The successful candidate will collaborate with NLR staff and researchers to develop agentic AI for the optimization of Fe‑N‑C catalyst synthesis. Responsibilities Development of agentic AI framework that automates the training of MLIPs and the exploration of the combinatorial space of reactions relevant to Fe‑N‑C catalyst synthesis and their energetics Collaboration with NLR researchers to use the developed AI to study the chemistry of graphitization and Fe incorporation into the N-C matrix for different synthetic precursors, e.g. iron salts and zeolitic imidazolate framework (ZIF) linkers Development of AI that processes, analyzes, and visualizes results from simulations provide chemical insight and intuition into important chemical reactions Authoring, presenting and assisting in the preparation of technical papers, reports and conference proceedings on topics related to AI-automated MLIP studies of the synthesis of Fe‑N‑C fuel cell catalysts Working Arrangements This role will be a hybrid work arrangement primarily at our South Table Mountain campus with some work from home time. Basic Qualifications Minimum of a 3.0 cumulative grade point average. Undergraduate: Must be enrolled as a full-time student in a bachelor’s degree program from an accredited institution. Post Undergraduate: Earned a bachelor’s degree within the past 12 months. Eligible for an internship period of up to one year. Graduate: Must be enrolled as a full-time student in a master’s degree program from an accredited institution. Post Graduate: Earned a master’s degree within the past 12 months. Eligible for an internship period of up to one year. Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution. Must meet educational requirements prior to employment start date. Additional Required Qualifications Excellent written and verbal communication skills. Excellent knowledge of AI automation, including skills files and deterministic frameworks such as LangChain. Experience with chemistry and materials science, especially with incorporation of ML/AI into the workflow. Experience with creating python environments for AI/ML tasks and workflows Preferred Qualifications AI workflow automation of MLIP calculations for exploration of the chemical space relevant to Fe‑N‑C catalyst synthesis. Experienced running density functional theory (DFT) software packages such as JDFTx or VASP. Experience with the MACE-based machine-learned interatomic potentials, especially foundational models. Salary Annual Salary Range: $44,500 - $71,200 Benefits Summary Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Badging Requirement NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement. Drug Free Workplace NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug. If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn. Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. #J-18808-Ljbffr NREL