Principal Research Scientist at well-funded industrial AI startup
About The Position
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. Why this role is remarkable: 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.
Requirements
- 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.
Responsibilities
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
Ph.D. or professional degree
