Co-Op, AI-Driven Equation Discovery

The role

You will develop and benchmark methods to extract interpretable governing equations from experimental data. You will work with electrochemistry, formulations, and advanced materials datasets to build equation discovery pipelines.

What you will do

• Build end-to-end equation discovery pipelines from preprocessing through candidate generation and validation
• Benchmark symbolic regression methods on Lila campaign data
• Apply equation discovery to live electrochemistry, formulation, and materials datasets
• Design evaluation harnesses measuring recovery rate, generalization, noise robustness, and physical consistency
• Embed discovered equations into surrogate models, physics-informed models, and experimental digital twins
• Translate open scientific questions into concrete problems with datasets, baselines, and success criteria
• Document and present findings across PS AI and domain science teams

Required qualifications

• Pursuing a Master's or PhD in ML, CS, applied math, physics, materials science, or chemical engineering
• Strong Python skills with hands-on experience in PyTorch, JAX, or similar
• Experience applying machine learning to messy, real-world scientific or experimental data
• Solid grounding in linear algebra, calculus, and probability
• Comfort reading and implementing methods from ML research papers
• Ability to frame open-ended scientific questions as concrete ML tasks
• Clear communication across research, engineering, and physical science teams

Nice to have

• Working knowledge of symbolic or sparse regression methods (SINDy, PySR, PDE-FIND, or equivalent)
• Experience with LLM-guided or agentic symbolic regression (LLM-SR, SR-Scientist, or similar)
• Background in physics-informed ML, uncertainty quantification, or operator learning (PINNs, neural ODEs, FNO, DeepONet)
• Exposure to digital twin or closed-loop workflows: model calibration, active learning, Bayesian optimization
• Domain knowledge in electrochemistry, formulations, superconductors, or materials science

About the company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science.