Power Systems Research Scientist
Gridmatic · Cupertino · $175,000–$270,000 (stated in the posting)
The Role
We are looking for a Power Systems Research Scientist to develop physics-based models of large-scale transmission systems and their impact on electricity markets.
You will work on large-scale optimization and simulation problems, including power flow, congestion, and security-constrained unit commitment and economic dispatch (SCUC/SCED). This role focuses on designing scalable algorithms and high-performance implementations for solving complex power system problems.
This role sits at the core of our research and trading stack, building models and computational tools that directly impact how we understand and operate in electricity markets.
We are particularly interested in rethinking power system optimization and simulation using modern computing (e.g., GPU acceleration).
What you'll do:
- Develop and analyze power network models, including AC/DC power flow, contingency analysis, and security constraints
- Build and enhance large-scale optimization models (e.g., SCUC/SCED) with detailed transmission constraints
- Design and implement scalable algorithms and solver components for large-scale power system optimization
- Identify and address computational bottlenecks in network-constrained simulations and optimization
- Model and analyze congestion and transmission-driven market outcomes
- Simulate grid scenarios with high penetration of renewables, storage, and outages
- Collaborate with ML and trading teams to integrate network-aware signals into forecasting and decision systems
Qualifications:
- Advanced degree (MS/PhD) in Electrical Engineering, Power Systems, or related field
- Strong background in power systems analysis and modeling
- Experience with power flow (AC/DC), transmission modeling, and congestion analysis
- Familiarity with ISO/RTO markets and network-constrained market outcomes
- Experience with optimization algorithms and large-scale mathematical programming
- Understanding of numerical methods for convex and/or non-convex optimization
- Strong programming skills in Python
Nice to Have:
- Experience with tools such as PSS/E, PowerWorld, PSLF, or similar
- Familiarity with SCUC/SCED implementations
- Background in electricity market modeling or trading
- Experience working with large-scale datasets and cloud applications
- Familiarity with key power systems concepts such as PTDFs (power transfer distribution factors) and security constraints
- Experience with GPU-accelerated computing for large-scale optimization or simulation
- Experience with frameworks such as PyTorch or JAX for high-performance numerical computing
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