Connect machine learning with numerical algorithms at NVIDIA, advancing solver performance for scientific, engineering, and industrial simulations. Apply Python and GPU computing to AI-native research.
This senior applied research scientist role focuses on ML methods inside and around numerical solvers. You will develop AI-guided multigrid, solver-in-the-loop learning, differentiable simulation, and hybrid numerical or ML methods. The work spans NVIDIA platforms, NVIDIA Research, universities, and industrial simulation teams.

Key Responsibilities

Research AI-assisted numerical methods for large-scale simulationsInvent learned preconditioners and AI-guided multigrid methodsBuild solver-in-the-loop pipelines using simulation dataMeasure convergence, robustness,



correctness, and end-to-end speedupCollaborate across NVIDIA numerical and simulation platformsRequirements:
PhD or equivalent experience in a related fieldFive years of relevant work or research experienceMachine learning and scientific computing backgroundExperience with PyTorch, JAX, Python, and GPU computingKnowledge of PDEs, sparse linear algebra, and iterative solversApply scientific machine learning, numerical algorithms, and GPU computing to NVIDIA’s AI-native solver research.
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📌 Senior Ai Numerical Methods Scientist (Winnipeg)
🏢 NVIDIA
📍 Winnipeg