Postdoctoral Appointee, GenAI - Hybrid (CA/NM)

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.

Are you looking to do creative and innovative research in cheminformatics, data, and predictive science? Do you want to increase your engagement with research that supports the development of material science and engineering? Sandia's Materials Lifecycle Management department is seeking a highly dedicated and innovative Postdoctoral Appointee to join the Material, Physical, and Chemical Sciences Center.

We are seeking a Postdoctoral Appointee/Scientist to apply electronic structure calculations, machine learning, and/or first principles simulations to accelerate materials discovery. Research areas may broadly span organic and inorganic materials modeling for hydrogen sinks, storage, or utilization), carbon capture, or other applications. A central theme in this effort is the rational design of new materials using existing, improved, and novel GenAI algorithms for generating new molecules or crystal structures and compositions or other nano- or macroscopic units. Excellent communication skills are required to convey results with multi-disciplinary scientific teams and help prioritize and direct experimental validation efforts.

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

• Demonstrate the creativity and know-how to utilize and develop GenAI models for finding novel materials of interests, develop new materials featurization strategies, and adapt state-of-the-art machine and deep learning techniques to directly predict materials properties that are not achievable within currently established methodologies.
• Use Density Functional Theory (or other first principles techniques) to acquire any data necessary to train such models when it does not already exist.
• Integrate the outputs of machine learning models with other physics-based models or classical simulations to predict the thermodynamic, kinetic, or electronic properties of materials.
• Mentor technologists and interns
• Work collaboratively to execute, track, and refine project plans with an integrated multi-disciplinary team that may include members from national labs, universities, and industry
• Communicate your research through writing scientific papers, publishing in peer-reviewed journals, and presenting findings at seminars and conferences
• Work to execute, monitor, and refine project plans and proposals

This position is eligible for telecommuting and the selected applicant must live within a reasonable distance for commuting to the assigned work location when necessary.

• PhD acquired within the last 5 years in or related to material science, engineering, applied mathematics, physics, chemistry, bioinformatics, computer science, machine learning, artificial intelligence, or related field with an emphasis on building, evaluating, and applying predictive models.
• Active learning, GenAI techniques to iteratively discover better materials
• Familiarity with interpretable machine learning techniques to discover new structure-function relationships from experimental or computational data
• Record of technical accomplishment and written communication as evidenced by publication in high-impact scientific journals
• Ability to obtain and maintain a DOE Q-Clearance

• Strong verbal communication and data presentation skills as demonstrated through scientific conference presentations
• Strong background in statistics, machine learning and data science with applications to engineering and scientific data analysis.
• Extensive collaboration skills within a larger team engaged in modeling, material synthesis, and use of advanced characterization tools.
• Strong programming and database skills (e.g., Python, R, C++, MySQL)

Sandia's Materials Lifecycle Management Department is a diverse team of engineers and scientists dedicated to teaming with both research and mission delivery organizations to address materials-based risks (i.e., quality, availability, compatibility and aging) and enable new material discovery. Our team provides a critical interface with the NNSA and engineering stakeholders through its leadership of the Aging & Lifetimes and At-Risk Materials programs enabling informed engineering design decisions. We develop scalable, FAIR data management solutions to empower AI/ML research, assess material compatibility, manage the Granta data based, its material records, and new material data ingestion, and utilize and develop GenAI models for finding novel, application specific materials. This department has a strong record of delivering critical materials information to broad internal and external stakeholders that improves SNLs and the broader Nuclear Security Enterprises (NSE) mission delivery.

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.

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.

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.

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.