Physics Informed Neural Networks Jobs in California

... physics-informed neural networks--to accelerate simulations, enhance efficiency, drive novel improvements, increase part yield, reduce inspection burden, and optimize parts. • Collaborate with ...

... physics-informed neural networks--to accelerate simulations, enhance efficiency, drive novel improvements, increase part yield, reduce inspection burden, and optimize parts. • Collaborate with ...

... physics-informed neural networks--to accelerate simulations, enhance efficiency, drive novel improvements, increase part yield, reduce inspection burden, and optimize parts. • Collaborate with ...

... networks, physics-informed neural networks, or other surrogate model architecture • Experience solving inverse problems such as geometry optimization or design under uncertainty • Strong ...

Leverage machine learning and AI solutions-such as surrogate modeling and physics-informed neural networks-to accelerate simulations, enhance efficiency, drive novel improvements, increase part yield ...

Leverage machine learning and AI solutions-such as surrogate modeling and physics-informed neural networks-to accelerate simulations, enhance efficiency, drive novel improvements, increase part yield ...

Leverage machine learning and AI solutions-such as surrogate modeling and physics-informed neural networks-to accelerate simulations, enhance efficiency, drive novel improvements, increase part yield ...

... physics-informed neural networks Preferred : • Hands-on experience with CFD or FEM solvers • Experience with geometry kernels or parametric CAD APIs • Background in differentiable simulation or ...

Experience with Graph Neural Networks, Physics-Informed Neural Networks, Neural Operators, and Transformer architectures * System-Level Thinking: Experience with cloud computing platforms (AWS, GCP ...

As a bonus, you may have experience working with hardware-in-the-loop training, mixed-signal hardware, quantization, or physics-informed neural networks Company : Unconventional AI rethinks computer ...

... or physics-informed neural networks • Experience with differentiable simulation or differentiable rendering • Hands-on experience with CFD, FEM, or mesh generation • Contributions to open ...

Expert-level understanding of at least one modern architecture class such as Fourier Neural Operators (FNO), neural operators, MeshGraphNet, Transolver, graph neural networks, physics-informed neural ...

Expert-level understanding of at least one modern architecture class such as Fourier Neural Operators (FNO), neural operators, MeshGraphNet, Transolver, graph neural networks, physics-informed neural ...

Expert-level understanding of at least one modern architecture class such as Fourier Neural Operators (FNO), neural operators, MeshGraphNet, Transolver, graph neural networks, physics-informed neural ...

Suggest ideas to drive the AI strategy for engineering design, with a focus on physics-informed neural networks (PINNs), digital twins, and high-fidelity model surrogates. * Research and test new AI ...

Develop surrogate models (e.g., physics-informed neural networks, neural operators, graph neural networks) that approximate high-fidelity simulations at orders-of-magnitude lower cost. * Integrate ...

Preferred : • Experience GPU-accelerating CFD/FEA solvers, or developing physics-ML and surrogate models (NVIDIA PhysicsNeMo/Modulus, physics-informed neural networks). • Experience with NVIDIA ...

Develop surrogate models (e.g., physics-informed neural networks, neural operators, graph neural networks) that approximate high-fidelity simulations at orders-of-magnitude lower cost. * Integrate ...

Implement surrogate models, physics-informed neural networks, or generative approaches for scientific problems * Develop data pipelines and frameworks for scientific machine learning across ...

... graph neural networks, diffusion models, or related architectures. * Working knowledge of ... Published work in physics-informed ML, neural operators, scientific machine learning, or related ...