Acceler8 Talent

Develop and validate physics-based power-system simulations that combine numerical solvers with machine learning. | Seeks experience in power systems and scientific ML, strong Python or C++ skills, and familiarity with ML frameworks and numerical methods. | I'm working with an early-stage AI company combining machine learning and electrical/power simulation to solve complex engineering challenges. They're looking for Applied AI Engineers and Researchers with experience in power systems, electrical engineering and scientific computing. The role: • Develop physics-based models for electrical and power systems. • Combine numerical solvers with machine learning to improve simulation speed and accuracy. • Build AI models for power-flow, converter dynamics and electromagnetic simulations. • Validate models against real-world measurements and established baselines. • Develop reliable scientific ML tools for engineering applications. What they're looking for: • Experience in power-flow modelling, grid interconnection/protection, power electronics, converter dynamics or electromagnetics. • Hands-on experience combining machine learning with numerical simulation. • Strong Python or C++ programming skills. • Familiarity with PyTorch, JAX or other scientific ML frameworks. • Understanding of numerical methods and physical model validation. Why consider it? • Join an early-stage AI company developing technology for complex engineering systems, with initial applications in AI data-centre power infrastructure. Location: Cambridge, MA | Hybrid (3 days onsite). Remote flexibility for exceptional candidates. Interested? Apply directly or message me for a confidential discussion.