Sandia Biotech, Inc
1 week ago
Postdoctoral Appointee in Atomistic Modeling and Machine Learning for Catalysis Sandia National Laboratories in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Postdoctoral position at Sandia National Laboratories; temporary appointment for up to one year with possible renewal at Sandia's discretion for up to five additional years. The posting mentions Sandia benefits such as medical/dental/vision insurance, paid time off, 401(k), and telecommuting arrangements, but no stipend or salary amount is stated.
Country
United States
University
Sandia Biotech, Inc

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About this position
Sandia National Laboratories is advertising a Postdoctoral Appointee in Atomistic Modeling / Machine Learning for its Computational Materials Science Department. The role focuses on combining density functional theory (DFT), machine learning (ML/AI), and atomistic simulation to accelerate multiscale modeling of reactive systems and catalysis.
Research activities include building a high-throughput DFT workflow to sample chemical reactions, developing ML frameworks to predict reaction events, integrating those models with molecular dynamics tools such as LAMMPS, and conducting atomistic simulations of catalysis in complex materials. The team works across materials discovery and design, with expertise spanning metals, polymers, ceramics, composites, ferroelectrics, and metal-organic frameworks.
Eligibility highlights: applicants must hold a PhD in Materials Science, Physics, Chemistry, Mechanical Engineering, or a closely related field. The selected candidate must be able to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship. The posting also notes that the position is hybrid.
Desired background includes experience with DFT codes such as VASP, Quantum Espresso, Gaussian, or DFTB+, ML/AI methods for atomistic simulation (including machine-learned interatomic potentials, graph neural networks, and atomic cluster expansion descriptors), and programming in Python and C++ with ML packages like PyTorch or TensorFlow. Experience with catalysis, adsorption, interfacial science, polymers, metals, or MOFs is especially relevant.
Funding and terms: this is a temporary postdoctoral appointment for up to one year, with possible renewal at Sandia's discretion for up to five additional years. No stipend or salary amount is listed in the post. Sandia highlights benefits such as medical/dental/vision insurance, paid time off, 401(k), learning opportunities, relocation assistance, and telecommuting arrangements where approved.
Location: Albuquerque, New Mexico, United States.
How to apply: submit an application through the Sandia job portal using the provided Apply Now link. The posting states it will remain open for at least three calendar days and may be extended. Applicants are also directed to review Sandia's resume writing best practices before applying.
Funding details
Postdoctoral position at Sandia National Laboratories; temporary appointment for up to one year with possible renewal at Sandia's discretion for up to five additional years. The posting mentions Sandia benefits such as medical/dental/vision insurance, paid time off, 401(k), and telecommuting arrangements, but no stipend or salary amount is stated.
What's required
PhD in Materials Science, Physics, Chemistry, Mechanical Engineering, or a closely related field. The selected candidate must be able to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship. Desired qualifications include expertise with DFT simulations and codes such as VASP, Quantum Espresso, Gaussian, or DFTB+, experience developing and applying ML/AI methods to atomistic simulation, proficiency in Python and C++, familiarity with PyTorch or TensorFlow, and experience with catalysis, adsorption, or interfacial science.
How to apply
Apply through the Sandia job portal using the posted Apply Now link. Review Sandia's resume writing best practices before submitting your application. The posting is open for at least three calendar days and may be extended.
More information can be found here
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