Postdoctoral Appointee - Atomistic Modeling/Machine Learning, Hybrid

Sandia National Laboratories; New Mexico; Hybrid; USD 70,000 - 90,000; Full time

Benefits offered by this job

Hybrid work arrangements

Relocation assistance

Comprehensive benefits

Job summary

Sandia National Laboratories invites applications for a Postdoctoral Appointee in Atomistic Modeling and Machine Learning. The role blends DFT-based simulations with ML to accelerate multiscale reactive-system modeling.

The selected candidate will implement high-throughput DFT workflows, develop ML/AI frameworks compatible with MD codes like LAMMPS, and collaborate across disciplines to advance materials design for national security.

Qualifications

• PhD in materials science, physics, chemistry, mechanical engineering, or closely related field.

Responsibilities

• Establish a high-throughput DFT workflow to sample chemical reactions.

Skills

Python

C++

ML/AI

Graph neural networks

DFT workflows

Education

PhD in Materials Science, Physics, Chemistry, Mechanical Engineering, or closely related field

Tools

VASP

Quantum Espresso

Gaussian

DFTB+

Job description

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Postdoctoral Appointee - Atomistic Modeling/Machine Learning, Hybrid

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 researcher with a background in density functional theory (DFT) and machine learning (ML) to join our multidisciplinary team of materials scientists. You bring passion for learning and energy for combining first-principles atomistic simulations with ML/AI to develop novel approaches accelerating multiscale simulation of reactive systems.

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

Establish a high-throughput workflow that uses DFT to sample chemical reactions.

Develop an ML/AI framework that can predict chemical reaction events and integrate that framework with molecular dynamics codes (i.e., LAMMPS).

Plan, conduct, and analyze atomistic simulations to study catalysis in complex material systems.

Integrate materials knowledge to formulate research hypotheses, propose and carry out research.

Work in collaborative team environments on multidisciplinary, technically challenging projects as part of a dynamic research organization.

Communicate accomplishments in presentations at conferences and publications in peer-reviewed journals and engage with program managers to convey impact and research direction.

Due to the nature of the work, the selected candidate must be able to work hybrid.

Qualifications We Require:

PhD in Materials Science, Physics, Chemistry, Mechanical Engineering, or closely related field.

Ability to obtain and maintain a DOE Q-level security clearance.

Qualifications We Desire:

Demonstrated expertise with DFT simulations and codes (e.g., VASP, Quantum Espresso, Gaussian, DFTB+, etc.).

Experience developing and applying state-of-the-art ML/AI architectures and approaches to atomistic simulation methods (e.g., machine-learned interatomic potentials, graph neural networks, atomic cluster expansion descriptors, etc.).

Proficiency with programming languages (e.g., Python, C++) and ML packages (e.g., PyTorch, TensorFlow).

Experience with atomistic simulations of catalysis, adsorption, and/or interfacial science (particularly involving polymers, metals, and/or MOFs).

Track record of collaborating with experimentalists and computational researchers to advance materials for engineering applications.

Strong written and verbal communication skills evidenced by a history of publishing original research in peer-reviewed journals and presentations at professional conferences.

Demonstrated ability to build effective working relationships and develop creative solutions in team environments.

About Our Team:

The Computational Materials Science Department applies materials modeling on multiple length scales to accelerate engineering solutions and drive materials discovery and design for Sandia missions. Our expertise spans a diversity of materials (including metals, polymers, ceramics, composites, ferroelectrics, and metal-organic frameworks) and a breadth of computational methods from density functional theory and molecular dynamics to mesoscale and microstructure-informed continuum simulations.

Posting Duration:

This posting will be open for application submissions for a minimum of three (3) calendar days, including the 'posting date'. Sandia reserves the right to extend the posting date at any time.

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:

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.

• Affordable housing, reasonable cost of living
• Minimal traffic congestion compared to larger cities
• At Sandia, recruiters manually review resumes on each job posting instead of using a resume screening software program
• By following the best practices outlined, this ensures that recruiters can accurately determine your qualifications for the position