PREP Research Associate in Physics, AI, and Digital Twins for Primary Standards George Washington University in United States

George Washington University and NIST are seeking a PREP Research Associate for the project “SI meets AI: Neural Network-powered Digital Twin for Advancing Primary Standards” in Gaithersburg, Maryland, United States.

This opportunity sits at the intersection of physics, artificial intelligence, computer science, electrical engineering, and materials science. The project focuses on building physics-informed digital twins for primary standards in mass, voltage, and resistance, with the goal of accelerating the development and commercialization of next-generation SI realizations.

Responsibilities include developing and implementing AI regression models for high-impact physical measurements, using Vision Transformers and CNNs for image classification of graphene data, building software for image reconstruction and system simulation, and preparing presentation materials for NIST and industry stakeholders.

Eligibility highlights: the post explicitly seeks a PhD candidate in Physics with 2+ years of relevant experience. Applicants should have strong skills in PyTorch, Python, advanced computer vision methods, and the ability to develop deployable scientific software.

No deadline, stipend, or funding package is specified in the post. Interested candidates should use the provided application link to review the posting and apply.