Sandia National Laboratories · 12 hours ago
Postdoctoral Appointee - AI/ML for Uncertainty Quantification, Onsite
Sandia National Laboratories is the nation’s premier science and engineering lab for national security and technology innovation, and they are seeking a highly motivated and driven postdoctoral appointee to join a multidisciplinary team. The role focuses on developing effective supervised and unsupervised learning algorithms for large-scale computational studies of phase field and polycrystalline structure evolution.
GovernmentInformation TechnologyNational Security
Responsibilities
Conduct research to develop effective supervised and unsupervised learning algorithms to facilitate large-scale computational studies of phase field and polycrystalline structure evolution
Qualification
Required
PhD in a field of physical sciences, applied mathematics, engineering, or other relevant field conferred within five years prior to employment
Knowledge and expertise in machine learning and/or uncertainty quantification
Knowledge and expertise in computational science and/or software development
Ability to obtain and maintain DOE Q-level security clearance
Preferred
Proficiency in using open-source machine learning libraries such as PyTorch or JAX for developing, training, and deploying advanced machine learning models tailored to complex scientific problems
Expertise in operator learning and generative models with a focus on their applications in the physical sciences
Experience with reduced order modeling and latent space representations
Strong programming skills in C++ and Python and integration of machine learning solutions into existing scientific workflows
Collaborative research experience
Excellent interpersonal and communication skills
Benefits
Generous vacation
Strong medical and other benefits
Competitive 401k
Learning opportunities
Relocation assistance
Amenities aimed at creating a solid work/life balance
Company
Sandia National Laboratories
Sandia is a conducts research and development into the non-nuclear components of nuclear weapons.
Funding
Current Stage
Late StageTotal Funding
$4.4MKey Investors
US Department of EnergyARPA-E
2023-09-21Grant· $0.5M
2023-07-27Grant
2023-01-10Grant· $3.7M
Leadership Team
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