Postdoctoral Appointee - Machine Learning and Molecular Dynamics, Onsite

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.

We are seeking a postdoctoral researcher with expertise in machine learning (ML), molecular dynamics (MD) simulations, and computational materials science to join our multidisciplinary team focused on advancing complex solvent-based separation systems. In this role, you will collaborate closely with synthetic chemists and experimentalists to develop fundamental insights into separations processes within multi-state materials systems.

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

• Design, perform, and analyze molecular scale simulations of nanoporous and/or liquid phase materials
• Leverage existing machine learning or artificial intelligence tools to create and analyze structure-property relationships based on experimental and modeling data
• Conduct work in a multi-disciplinary team environment by working closely with experimental and synthetic chemists
• Write research manuscripts and attend & present at technical conferences and/or program meetings

Due to the nature of the work, the selected applicant must be able to work onsite. This position is located in Albuquerque, NM, and the annual salary for this position is $100,500.

• PhD in materials science and engineering, chemistry, chemical engineering, physics, applied mathematics, computer science, data science, or other relevant, related field
• Demonstrated experience building, evaluating, and applying machine learning models (such as probabilistic surrogate models, active learning, and/or ML-enhanced atomistic potentials) to experimental and/or computational datasets
• Experience with molecular dynamics simulations and/or integration of ML methods with simulation tools
• Strong record of technical accomplishments and written communication, as evidenced by peer-reviewed publication(s)

• Strong verbal and written communication skills, with a proven ability to collaborate effectively in multidisciplinary team environments
• Familiarity with advanced ML/AI techniques such as generative adversarial networks, Bayesian deep learning, graph neural networks, atomic cluster expansion descriptors, or similar
• Experience developing machine-learning models to elucidate structure-property or structure-function relationships in porous materials, metal-organic frameworks (MOFs), porous liquids, or complex solvent systems (e.g., ionic liquids, deep eutectic solvents)
• Proficiency in programming and data management, particularly with Python-based data science tools, and familiarity with scientific data infrastructure and cloud computing environments
• Proven ability to build effective working relationships and contribute creative solutions within team settings
• Flexibility to work in a hybrid work environment, as required
• Ability to obtain and maintain DOE Q-level security clearance

Sandias Geomechanics and Geochemistry Department advances fundamental scientific understanding and develops innovative capabilities to address complex challenges in subsurface science, energy, national security, and environmental sustainability. The department integrates experimental investigations, advanced characterization, computational modeling, and engineering applications across multiple spatial and temporal scales.

Sandias geomechanics research addresses cross-cutting challenges in rock mechanics, rock mass characterization, deformation and failure processes, numerical modeling and simulation, material model validation, and subsurface monitoring. Integrating laboratory experiments, field observations, and computational simulations, key research areas include characterization of natural fracture systems; investigation and modeling of rock deformation and failure mechanisms; determination of thermomechanical, hydrological, and transport properties of rocks and fractures, including coupled processes; scaling of laboratory measurements to field conditions; in situ stress measurements and evaluation of subsurface boundary conditions; and laboratory- and field-scale validation of predictive models. These capabilities support applications in subsurface energy systems, critical mineral recovery, nuclear waste isolation, and national security.

Sandias geochemistry research focuses on understanding molecular-scale processes and chemical interactions at mineralfluid interfaces, including how chemical environments influence mineral reactivity, interfacial transport, and material behavior. Core capabilities span three complementary areas: (1) molecular-scale modeling and simulation, (2) experimental geochemistry, and (3) applied environmental and chemical engineering. By integrating molecular-level insights, laboratory experiments, and multiscale computational modeling, researchers develop and validate predictive models of complex geochemical processes. These capabilities support a broad range of applications, including critical mineral extraction and separation, subsurface energy resource recovery, nuclear waste management, environmental remediation, nuclear weapons applications, and contaminant detection and removal.

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.

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.

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.

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.