Artificial Intelligence and Computer Vision Materials Postdoctoral Research Associate

What You Will Do

The Materials Physics and Application Division – Center for Integrated Nanotechnologies (MPA-CINT) and Theoretical Division – Physics and Chemistry of Materials (T-1) at Los Alamos National Laboratory seek a highly motivated post‑doctoral candidate in the areas of Computer Vision (CV), Artificial Intelligence (AI), and materials modeling, with an emphasis on characterizing micrographs/radiographs using computer vision and AI. Successful applicants will work in Group CINT of the Materials Physics and Application Division and collaborate with a larger group of scientists and postdocs from across organizations.

This postdoctoral position is part of a larger project that focuses on developing and utilizing computer vision models for characterizing materials micrographs/radiographs and classifying defects, interfaces, and joints. The goal is to connect imaging‑derived features to materials structure‑property relationships. The successful applicant will be expected to integrate broadly with the project team, coordinate with experimentalists, publish results in peer‑reviewed journals, and present at prominent conferences.

The Laboratory offers unique opportunities for cross‑disciplinary collaborations, scientific workshop organization, conference attendance, and the possibility of nomination for LANL‑funded fellowships to support independent research.

• Develop and apply computer vision models for segmentation and classification of defects, interfaces, and joints in materials micrographs/radiographs.
• Train and optimize AI models using frameworks such as PyTorch or Tensor Flow.
• Integrate imaging data with materials modeling and atomistic simulation data to elucidate structure‑property relationships.
• Collaborate closely with experimentalists and cross‑disciplinary partners to design experiments and interpret results.
• Publish scientific findings in peer‑reviewed journals and present at conferences and workshops.
• Organize scientific workshops and support conference attendance for the team.

• Demonstrated expertise in one or more of the following:
  • Advanced CV/AI for materials micrographs, including segmentation/classification of defects, interfaces, and joints (e.g., U‑Net, Mask R‑CNN, Vision Transformers).
  • Experience training AI models with PyTorch or Tensor Flow.
  • Materials modeling or atomistic simulation experience relevant to mechanics (e.g., MD/DFT, microstructure‑property relationships, defect physics).
  • Strong programming skills in Python (mainly scikit‑image, OpenCV).
• Demonstrated experience in conducting original scientific research with a peer‑reviewed publication record.
• Excellent oral and written communication skills.
• A STEM PhD in Materials Science, Computational Physics, Engineering, or related fields, completed within the last five years or soon to be completed.

• Solid background in materials science and engineering.
• Experience training AI and CV models on GPU‑accelerated supercomputers with large workloads, familiarity with PyTorch Lightning, Hugging Face, Lang Chain, etc.
• Ability to adapt to new research requirements and learn new areas quickly.
• Team‑orientated mode of working within a multi‑disciplinary environment and interacting with people of diverse expertise.

Employment Status:
Full‑time or part‑time options available.

Work Location:

Onsite in Los Alamos, NM. All work locations are at the discretion of management.

Contact:
Dr. Avanish Mishra – avanish
Dr. Saryu Fensin – saryuj

Equal Opportunity
Los Alamos National Laboratory is an equal opportunity employer. All employment practices are based on qualification and merit, without regard to protected categories such as race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal, state, and local laws and regulations.

The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. To request an accommodation, please email applyhelp or call (505)‑664‑6947.