Sort by
Refine Your Search
-
-fidelity optimization, neural architecture search, or large-scale AutoML systems. Familiarity with surrogate modeling, physics-informed neural networks, or uncertainty quantification for scientific
-
loads, transmission networks, etc. Develop simulation algorithms that enable large-scale simulations. Integrate (or co-simulate) grid component/device models into open-source software tools for integrated
-
Requirements: The prospective candidate should be well-versed with deep neural networks, have experience working on PyTorch or similar DL frameworks, programming in Python (preferred), NLP packages and pipelines
-
such as classifier free guided diffusion models, transformers with multi-headed attention, physics-informed neural networks, materials foundational models with multi-task learning, symbolic regression
-
CPU and GPU based HPC systems. Exploration of the capabilities of DPU/IPU SmartNICs to support network security isolation, platform level root-of-trust, and secure platform management/partitioning