Postdoctoral AI Researcher in Power Systems
Tasks
- Create benchmarks for models
- Develop graph-based machine learning models
- Extend GridFM capabilities for distribution networks
- Generate training data
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Agent systems | CI/CD | CPLEX | Cloud Computing | Contingency analysis | Decision analytics | Decision support | Deep learning | Distributed Computing | Docker | Fine Tuning | Foundation Models | GPU Computing | Git | Graph Neural Networks | Graph transformers | Grid planning | GridLAB-D) | Gurobi | High Performance | High-Performance Computing | Integer Programming | JAX | JuMP | LLM workflows | Machine Learning | Machine Learning Pipelines | Mathematical Optimization | Matpower | Mixed Integer | Mixed-Integer Programming | Model Deployment | Model Evaluation | Model Fine-tuning | Model Robustness | Model Training | Multi-Agent | Multi-Agent Systems | Neural Networks | OpenDSS | Optimal Power Flow | PSS/E | Performance Computing | Physics-informed AI | Power Flow | PowerModels | PyTorch | Pyomo | Reproducible Workflows | Retrieval systems | Stochastic Optimization | TensorFlow | Tool-Calling | Tool-calling Agents | Uncertainty Quantification
Education
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