Principal Research Scientist at well-funded industrial AI startup

You will lead the advancement of scientific foundations by merging physics with deep learning for real-time energy and industrial applications. This role bridges the gap between high-level research and production-grade systems, tasking you with developing hybrid models and neural operators that deliver measurable operational value across large-scale physical systems.

Well-funded industrial AI startup

• Lead research initiatives on physics-informed ML, hybrid modeling, and neural operators to optimize complex industrial systems.
• Design and evaluate rigorous experiments, quantifying performance improvements against operational metrics and baseline datasets.
• Partner with engineering and product teams to productionize research outcomes, ensuring reproducibility and scalability in deployment.

• Holds a PhD in Computer Science, Physics, or Applied Mathematics with a strong record of publications at top-tier venues like NeurIPS or ICML.
• Possesses deep technical expertise in Python and frameworks such as PyTorch, JAX, or TensorFlow, alongside experience with scalable ML tools.
• Demonstrates a proven ability to bridge the gap between academic research and practical constraints within energy or industrial contexts.

===

• Influence the cutting edge of physics-informed machine learning by applying theoretical breakthroughs to tangible, real-world industrial challenges.
• Join a high-calibre team backed by top-tier VCs, operating at the intersection of computational modeling and scalable AI infrastructure.
• Take ownership of the full research lifecycle, from designing novel algorithms to seeing them deployed in mission-critical production environments.