Sort by
Refine Your Search
-
operando experiments under electrical, thermal, or mechanical bias to capture real-time defect dynamics. Integrate multimodal datasets and collaborate with AI/ML teams for data fusion, physics-informed model
-
://arxiv.org/abs/2509.00098 ) This project sits at the intersection of artificial intelligence and materials characterization and modeling. The goal is to create an AI system that can intelligently operate
-
specifically on developing machine learning-based surrogates and emulators for the dynamics of power grids. This role involves creating advanced probabilistic models that capture the complex behaviors
-
applications. With guidance, the appointee will: Develop advanced multiscale, multiphysics simulation tools relevant to the modeling of processes involving combined nuclear, chemical, and electrochemical
-
) simulations and reduced order modeling of turbulent and reacting flows relevant to advanced propulsion and power generation systems, such as gas turbines and detonation engines. The successful candidate’s
-
Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
-
foundational models to describe IDP interactions under various physiological conditions, both normal and cancer related Use these models to iteratively design, validate, and refine experiments, leading
-
models for microelectronics materials Curate, manage, and integrate heterogeneous datasets from experiments and simulations Collaborate closely with experimental teams to benchmark and refine computational
-
material property database for composites. The candidate will utilize the database to develop AI models for composite discovery. The candidate will work with a multidisciplinary team to set up finite element
-
modeling is a benefit, ideal candidates will be expected to work together with domain experts rather than possess all required expertise themselves. Beyond the listed projects, the candidate will be able