Postdoctoral Appointee - AI and Computational Materials Science

About Sandia

Sandia National Laboratories is the nation’s premier science and engineering lab for national security and technology innovation, with teams of specialists focused on cutting-edge work in a broad array of areas. Some of the main reasons we love our jobs:

• Challenging work with amazing impact that contributes to security, peace, and freedom worldwide
• Extraordinary co-workers
• Some of the best tools, equipment, and research facilities in the world
• Career advancement and enrichment opportunities
• Flexible work arrangements for many positions include 9/80 (work 80 hours every two weeks, with every other Friday off) and 4/10 (work 4 ten-hour days each week) compressed workweeks, part-time work, and telecommuting (a mix of onsite work and working from home)
• Generous vacation, strong medical and other benefits, competitive 401k, learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance*
  
  

World-changing technologies. Life-changing careers. Learn more about Sandia at: http://www.sandia.gov

• These benefits vary by job classification.
  
  

What Your Job Will Be Like

We are seeking a Postdoctoral Appointee to join our AI and Computational Materials Science team at the Center for Integrated Nanotechnologies. This role is dedicated to the development and implementation of Scientific Machine Learning (SciML) frameworks to solve complex problems in materials reliability and physical sciences. You will work at the cutting edge of "AI-for-Science," bridging the gap between traditional governing equations (PDEs/ODEs) and modern deep learning architectures.

You will be responsible for designing AI-ready data pipelines that ingest heterogeneous data ranging from high-fidelity Molecular Dynamics (MD), Discrete Dislocation Dynamics, and Phase Field outputs to experimental microscopy and sensor streams to build predictive models for materials aging. This work requires being located (or relocating) in Albuquerque, New Mexico, to participate in our vibrant, interdisciplinary research community at Sandia National Laboratories and CINT.

On any given day, you may be called on to:

• Develop and deploy Physics-Informed Neural Networks (PINNs), Deep Operator Networks (DeepONets), or Fourier Neural Operators (FNOs) to accelerate materials simulations.
• Build and operate automated, AI-mediated ingestion pipelines for large-scale scientific datasets generated by HPC clusters and experimental instruments.
• Design surrogate models and digital twins that account for uncertainty quantification (UQ) in materials reliability and degradation.
• Implement high-performance ML workflows using PyTorch in a massively parallel computing environment.
• Collaborate with domain scientists, experimentalists, and infrastructure engineers to curate FAIR-compliant (Findable, Accessible, Interoperable, Reusable) datasets.
• Publish your research in premier AI and materials science journals and present at conferences such as NeurIPS, ICML, or MRS.
  
  

Due to the nature of the work, the selected applicant must be able to work onsite.

Qualifications We Require

• You have, or are pursuing, a PhD in Applied Mathematics, Computer Science, Applied Physics, Materials Science, or a related science/engineering field. PhD must be conferred within 5 years of employment.
• Demonstrated expertise in Scientific Machine Learning (SciML) specifically applied to physical, chemical, or materials science problems.
• Strong proficiency in PyTorch or equivalent deep learning frameworks for developing custom neural architectures.
• A significant track record of research excellence, evidenced by peer-reviewed publications and presentations in computational or data-driven science.

Discover our full range of relocation jobs with comprehensive support packages to help you relocate and settle in your new location.

• Excellent written and verbal communication skills for collaborating in a multidisciplinary team environment.
  
  

Qualifications We Desire

• Experience in building and maintaining production-level data pipelines or scientific or engineering data.
• Knowledge of advanced AI-mediated data curation techniques, such as automated annotation, feature extraction, and dataset fingerprinting.
• Familiarity with version control for models and datasets.
• Experience with High-Performance Computing (HPC) and distributed training of large-scale models using frameworks like Horovod or PyTorch Distributed.
• Background in Uncertainty Quantification (UQ) and Bayesian inference within the context of physical modeling.
• Ability to work effectively in a dynamic environment, guiding technical decisions and contributing to the strategic growth of the group's AI portfolio.
  
  

About Our Team

Our department supports the Center for Integrated Nanotechnology (CINT). CINT is a Department of Energy/Office of Science Nanoscale Science Research Center operating as a national user facility devoted to establishing the scientific principles that govern the design, performance, and integration of nanoscale materials. Through its core facility in Albuquerque and gateway facility in Los Alamos, CINT provides users from academia, industry, and government labs open access to the tools and expertise needed to explore the continuum from scientific discovery to the integration of nanostructures into the micro- and macro world. CINT is an equal partnership between Sandia National Laboratories and Los Alamos National Laboratory.

Posting Duration

Interested in relocating to United State? Check out our comprehensive Relocation Jobs in United State page with detailed relocation packages and benefits.

This posting will be open for application submissions for a minimum of seven (7) calendar days, including the ‘posting date’. Sandia reserves the right to extend the posting date at any time.

Security Clearance

This position does not currently require a Department of Energy (DOE) security clearance.

Sandia will conduct a pre-employment drug test and background review that includes checks of personal references, credit, law enforcement records, and employment/education verifications. Furthermore, employees in New Mexico need to pass a U.S. Air Force background screen for access to Kirtland Air Force Base. Substance abuse or illegal drug use, falsification of information, criminal activity, serious misconduct or other indicators of untrustworthiness can cause access to be denied or terminated, resulting in the inability to perform the duties assigned and subsequent termination of employment. Under federal law, citizens and agents of the People's Republic of China, the Islamic Republic of Iran, the Democratic People's Republic of North Korea, and the Russian Federation are generally prohibited from accessing Sandia National Laboratories. Accordingly, such individuals will not be considered for employment unless they are also a citizen of the United States.

If hired without a clearance and it subsequently becomes necessary to obtain and maintain one for the position, or you bid on positions that require a clearance, a pre-processing background review may be conducted prior to a required federal background investigation. Applicants for a DOE security clearance need to be U.S. citizens. If you hold more than one citizenship (i.e., of the U.S. and another country), your ability to obtain a security clearance may be impacted.

Members of the workforce (MOWs) hired at Sandia who require uncleared access for greater than 179 days during their employment, are required to go through the Uncleared Personal Identity Verification (UPIV) process. Access includes physical and/or cyber (logical) access, as well as remote access to any NNSA information technology (IT) systems. UPIV requirements are not applicable to individuals who require a DOE personnel security clearance for the performance of their SNL employment or to foreign nationals. The UPIV process will include the completion of a USAccess Enrollment, SF-85 (Questionnaire for Non-Sensitive Positions) and OF-306 (Declaration of for Federal Employment). An unfavorable UPIV determination will result in immediate retrieval of the SNL issued badge, removal of cyber (logical) access and/or removal from SNL subcontract. All MOWs may appeal the unfavorable UPIV determination to DOE/NNSA immediately. If the appeal is unsuccessful, the MOW may try to go through the UPIV process one year after the decision date.

Eeo

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status and any other protected class under state or federal law.

NNSA Requirements For MedPEDs

If you have a Medical Portable Electronic Device (MedPED), such as a pacemaker, defibrillator, drug-releasing pump, hearing aids, or diagnostic equipment and other equipment for measuring, monitoring, and recording body functions such as heartbeat and brain waves, if employed by Sandia National Laboratories you may be required to comply with NNSA security requirements for MedPEDs.

If you have a MedPED and you are selected for an on-site interview at Sandia National Laboratories, there may be additional steps necessary to ensure compliance with NNSA security requirements prior to the interview date.

Position Information

This postdoctoral position is a temporary position for up to one year, which may be renewed at Sandia's discretion up to five additional years. The PhD must have been conferred within five years prior to employment.

Individuals in postdoctoral positions may bid on regular Sandia positions as internal candidates, and in some cases may be converted to regular career positions during their term if warranted by ongoing operational needs, continuing availability of funds, and satisfactory job performance.

Job ID: 697158

Job Family: 92

Regular/Temporary Position: T

Full/Part-Time Status: F