Postdoctoral Appointee - Scientific Machine Learning for Surrogate Modeling and Power Grid Dynamics
UChicago Argonne(5 months ago)
About this role
A Postdoctoral Appointee in the Mathematics and Computer Science Division will conduct research in scientific machine learning to develop ML-based surrogates and emulators for power grid dynamics. The role focuses on creating probabilistic models of dynamical systems and integrating them into large-scale optimization workflows, with an emphasis on trustworthy, scalable computation on DOE leadership computing resources.
Required Skills
- Python
- C++
- Machine Learning
- Dae Modeling
- High-Performance Computing
- Distributed Computing
- GPU Training
- Numerical Optimization
- PyTorch
- JAX
+5 more
Qualifications
- PhD in Computer Science, Electrical Engineering, Applied Mathematics, or Related Field
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