Postdoctoral Appointee – Building Agentic AI Platform for X-ray Science

Postdoctoral Appointee – Building Agentic AI Platform for X-ray Science

We are seeking a highly motivated and creative Postdoctoral Researcher to join the X-ray Science Division (XSD) at Argonne National Laboratory. The successful candidate will develop web-based AI agents for X-ray spectroscopy by integrating large language models (LLMs) with physics-aware spectroscopy workflows. The researcher will work closely with a multidisciplinary team of X-ray physicists and computational scientists to advance a next-generation, user-friendly, agentic AI platform for automated data analysis, interpretation, and user interactions. The appointment is expected to last two years and the contract is extended on a yearly basis.

Application Materials - Please submit:

• CV and cover letter
• Name your documents using the following formats, e.g., “Firstname_Lastname_CV”, “Firstname_Lastname_cover_letter”.
• Include links to code examples in your CV (e.g., GitHub page, past project repositories).

Position Requirements

• A recent PhD (completed within 5 years, or soon to be completed) in computer science, engineering, computational science, a physical science (materials science, chemistry, physics etc.), or related field.
• Hands-on experience with AI frameworks and employing large language models.
• Strong Python skills and familiarity with LLM APIs (e.g., OpenAI API), agent frameworks (e.g. LangChain), PyTorch, and the Python scientific stack (e.g., numpy, pandas, scikit-learn).
• Experience with front-end development and web-based applications, back-end services and API design (e.g., FastAPI, Flask), and deploying applications in local or cloud environments.
• Experience working with large-scale datasets.
• Willingness to learn basic domain-specific X-ray science and basic materials knowledge, and a strong passion for applying agentic AI to scientific discovery.
• Effective written and oral communications skills.
• Demonstrated ability to work both independently and collaboratively in a multidisciplinary environment.
• Commitment to Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
• Interpersonal skills, oral and written communication skills, and ability to interact with people at all levels both within and outside the laboratory.

Preferred Knowledge, Skills, and Experience

• Experience in the following areas is preferred and will help the candidate succeed: X-ray absorption spectroscopy theory and modelling, and handling large synchrotron/X-ray datasets.
• Experience with vector databases (e.g. Pinecone) for Retrieval-Augmented Generation (RAG).
• Experience with prompt engineering and chain-of-thought techniques.
• Experience with multimodal AI and/or foundation models.

Job Family: Postdoctoral

Job Profile: Postdoctoral Appointee

Worker Type: Long-Term (Fixed Term)

Time Type: Full time