Postdoctoral Appointee - Machine Learning and Molecular Dynamics, Onsite

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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 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.

Qualifications We Require:

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)

Qualifications We Desire:

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

About Our Team:

Sandia's 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.

Sandia's…