Postdoctoral Research Associate - AI-Driven Analysis for Magnetic Quantum Materials

Oak Ridge National Laboratory • Oak Ridge, TN

34d • Onsite

About The Position

We are seeking a Postdoctoral Research Associate to advance modeling and AI-driven analysis for magnetic quantum materials, with a focus on neutron scattering and related experimental data. This position resides in the Neutron Scattering Division, Neutron Sciences Directorate at Oak Ridge National Laboratory (ORNL) and is embedded in the MAIQMag (Multimodal AI for 2D Quantum Magnets) collaboration. While located at the facility, the role is not primarily experimental; instead, the successful candidate will develop forward models, synthetic datasets, and AI tools that connect magnetic Hamiltonians to real experimental observables with a strong connection to facility instruments. As a postdoctoral fellow, you will join a team whose research interests include quantum spin liquids, frustrated magnetism, excitonic magnets, and strongly correlated electron systems. You will work closely with theorists, experimentalists, and computer scientists to build robust, scalable workflows that enable reliable extraction of magnetic interactions from neutron and complementary measurements in a high-performance computing environment.

Requirements

• PhD in physics, materials science, applied mathematics, computer science, or a related field, and no more than five years of experience beyond PhD.

Nice To Haves

• Background in quantum magnetism, neutron or X-ray scattering, or strongly correlated materials.
• Experience with computational / theoretical modeling and scientific programming (e.g. Julia, Python, C/C++).
• Familiarity with high-performance computing environments.
• Interest or experience in machine learning, inverse problems, or AI for scientific data.
• Strong record of research productivity and ability to work effectively in a collaborative, multi-disciplinary team.

Responsibilities

• Develop and apply computational models for quantum magnets and neutron scattering observables.
• Generate, document, and manage synthetic datasets (e.g. S(Q,ω), diffraction, thermodynamic data) for AI training and validation.
• Implement and optimize data representations and pipelines suitable for machine learning and uncertainty quantification.
• Collaborate with AI/ML experts to design and test inference methods that map experimental / synthetic data to underlying Hamiltonians.
• Publish scientific papers resulting from this research and present results at appropriate national and international meetings.
• Deliver ORNL's mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service.
• As a member of the ORNL scientific community, you will be expected to commit to ORNL's Research Code of Conduct.

Benefits

• Prescription Drug Plan
• Dental Plan
• Vision Plan
• 401(k) Retirement Plan
• Contributory Pension Plan
• Life Insurance
• Disability Benefits
• Generous Vacation and Holidays
• Parental Leave
• Legal Insurance with Identity Theft Protection
• Employee Assistance Plan
• Flexible Spending Accounts
• Health Savings Accounts
• Wellness Programs
• Educational Assistance
• Employee Discounts

What This Job Offers

• Career Level: Entry Level
• Industry: Professional, Scientific, and Technical Services
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees