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Sandia National Laboratories R&D - Machine Learning for Materials Science (Mid-Career) in Livermore, California


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.


We are seeking an R&D Materials Scientist to develop material solutions for a variety of problems related to energy storage and production, electronic/optical materials, and national security challenges. Specific research areas may include materials development for solid-state hydrogen storage and production, elucidation of corrosion mechanisms, prediction of phase transitions, and discovery of next-generation materials for microelectronics.

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

  • Use interpretable machine learning techniques to discover new structure-function relationships, which will in turn be used to design materials with properties and behaviors that are superior to existing options.
  • Conduct research that would involve extensive collaboration with team members engaged in modeling, materials synthesis, and the use of advanced characterization tools.
  • Play a major role in database development to enable the application of state-of-the-art machine learning and computational tools to complex materials science problems. This will include the use of both commercial software, such as Granta MI, and free/open source solutions.
  • Develop and/or apply machine learning methodologies that facilitate simulation-based material property predictions, which may otherwise be intractable for traditional approaches.


  • Doctoral degree in a relevant STEM field (e.g. materials science and engineering, chemistry, or physics) with emphasis on applying machine learning, data science, or other theory and computational methods to materials science problems.
  • Experience with one or more of the following computational techniques: machine learning, artificial intelligence, data science, graph theory, high-throughput screening and large scale computing environments.
  • Strong written and oral communication skills, as demonstrated by a record of first-author or coauthored scientific publications in peer-reviewed journals and presentations and scientific conferences.
  • Ability to hold a U.S. DOE Q security clearance


  • Ability to conduct creative, independent research in cross-disciplinary teams.
  • Knowledge and experience using data science and machine learning techniques for materials discovery and/or experience with explainable machine learning.
  • Experience with Granta MI, CKAN, Python, SOAP and REST APIs and/or with otherwise leveraging existing data sources.

Department Description:

The Energy Nanomaterials team is a research organization specializing in the synthesis and characterization of nanomaterials for energy and national security applications. Projects and capabilities in the department's research portfolio include nanoporous materials for sensing, catalysis, energy harvesting, and gas storage; materials for energy and hydrogen storage; thermoelectrics; and nanoscale materials characterization including extensive electron microscopy, atomic force microscopy, and nanoindentation instrumentation. The team is a key element in a diverse set of materials science organizations and resources, managed both locally and across the corporation. We partner broadly with other personnel within Sandia and many external institutions.

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 vacations, 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:

*These benefits vary by job classification.

Security Clearance:

Sandia is required by DOE to conduct a pre-employment drug test and background review that includes checks of personal references, credit, law enforcement records, and employment/education verifications. Applicants for employment need to be able to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship. 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.

Applicants offered employment with Sandia are subject to a federal background investigation to meet the requirements for access to classified information or matter if the duties of the position require a DOE security clearance. Substance abuse or illegal drug use, falsification of information, criminal activity, serious misconduct or other indicators of untrustworthiness can cause a clearance to be denied or terminated by DOE, resulting in the inability to perform the duties assigned and subsequent termination of employment.

EEO Statement:

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.


This Limited Term Employee (LTE) position is a temporary position for one year term, which may be renewed at Sandia's discretion up to a maximum of seven years.

Individuals in LTE 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.