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

Argonne National Laboratory; Lemont (IL); On-site; USD 72,879 - 121,465; Full time

Benefits offered by this job

Comprehensive benefits package

Collaborative work environment

Opportunities for scientific discovery

Job summary

Argonne National Laboratory is seeking a highly motivated Postdoctoral Researcher for the X-ray Science Division. This role involves developing an AI-enabled platform for X-ray absorption spectroscopy through integrating scientific machine learning techniques and computational chemistry expertise. The successful candidate will collaborate with a multidisciplinary team to further scientific discovery.

This position offers a competitive salary range from $72,879 to $121,465, based on experience and qualifications. Comprehensive benefits are included. Apply now to contribute to impactful research in a collaborative environment.

Qualifications

• Recent PhD (within 5 years) in computational chemistry or related field.
• Strong computational chemistry background and experience with DFT codes.
• Hands-on experience with Python and LLM APIs.

Responsibilities

• Develop an AI-enabled platform for X-ray absorption spectroscopy.
• Work with a multidisciplinary team on simulation and data analysis.
• Integrate LLMs and scientific machine learning into workflows.

Skills

Computational chemistry

DFT (Density Functional Theory)

Python programming

Experience with scientific datasets

Effective communication skills

Education

PhD in relevant field (computational chemistry, materials science, etc.)

Tools

VASP

Quantum ESPRESSO

Gaussian

Job description

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 an AI-enabled platform for X-ray absorption spectroscopy by integrating LLMs, scientific machine learning, physics-aware workflows, and strong computational chemistry/electronic-structure expertise. The researcher will work with a multidisciplinary team to advance agentic AI tools for simulation, interpretation, data analysis, and scientific discovery. The appointment is expected to last two years and the contract is extended yearly.

Position Requirements

• A recent PhD (within 5 years) in computational chemistry, chemistry, materials science, physics, computational science, computer science, engineering, or a related field.
• Strong computational chemistry background in atomistic simulations, electronic-structure theory, DFT, structure-property relationships, and interpretation of simulation results.
• Hands‑on experience with DFT or electronic-structure codes such as VASP, Quantum ESPRESSO, CP2K, ABINIT, GPAW, Gaussian, ORCA, Q-Chem, or related packages.
• Strong materials science or chemistry domain knowledge, such as bonding, defects, catalysis, batteries, solid‑state chemistry, molecular systems, or related materials classes.
• Strong Python skills and familiarity with LLM APIs, agent frameworks, PyTorch, and the Python scientific stack (e.g., NumPy, pandas, scikit‑learn).
• Passion for 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 with complex scientific datasets and reproducible analysis or simulation workflows.
• 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.

Preferred Knowledge, Skills, and Experience

• Experience with X-ray absorption spectroscopy theory, modelling, and interpretation, including XANES/EXAFS.
• Hands‑on experience with XAS simulation packages such as FEFF, OCEAN, FDMNES, XSpectra, or exciting.
• Experience comparing simulated and experimental XAS/EXAFS spectra.
• Experience with high‑throughput spectroscopy workflows, HPC, synchrotron datasets, or physics-informed AI.

Please include a cover letter that briefly describes relevant simulation, chemistry, AI/ML, and XAS experience; include code links if available.

The expected hiring range for this position is $72,879.00–$121,465.00. The pay offered to a selected candidate will be determined based on factors such as the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Comprehensive benefits are part of the total rewards package.

You will be asked to disclose any participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A, during the application phase for review by Argonne's Legal Department. All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case‑by‑case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.

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