Co-Op: AI-Driven Equation Discovery for Scientific ML

Lila Sciences, Inc.; Cambridge, San Francisco (MA, CA); Presencial; USD 41.000 - 55.000; A tiempo parcial

Descripción de la vacante

Lila Sciences, Inc. in Cambridge is seeking a Co-Op focused on AI-driven equation discovery to develop and benchmark methods that extract interpretable governing equations from experimental data, enabling physics-informed models and digital twins.

You will work with PS AI researchers and scientists, building end-to-end pipelines, benchmarking symbolic regression, and translating open scientific questions into concrete ML tasks, with opportunities to publish and present findings.

Formación

• 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

Responsabilidades

• Build end-to-end equation discovery pipelines from preprocessing through candidate generation and validation
• Benchmark symbolic regression methods (SINDy, PDE-FIND, PySR, LLM-guided search) 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

Conocimientos

Python

PyTorch

JAX

Machine learning

Educación

Master's or PhD in ML, CS, applied math, physics, materials science, or chemical engineering

Herramientas

PyTorch

JAX

Descripción del empleo

Lila Sciences, Inc. in Cambridge is seeking a Co-Op focused on AI-driven equation discovery to develop and benchmark methods that extract interpretable governing equations from experimental data, enabling physics-informed models and digital twins.

You will work with PS AI researchers and scientists, building end-to-end pipelines, benchmarking symbolic regression, and translating open scientific questions into concrete ML tasks, with opportunities to publish and present findings.