Co-Op, Agentic Simulations for Materials Science
MiddleOn-site (San Francisco)Salary undisclosed
Required Skills
Python
Job Description
Your Impact at LILA
Join our physical sciences team to contribute to developing ML- and agent-driven infrastructure that enables Lila's scientific superintelligence to autonomously construct, execute, and interpret complex physics simulations and apply these to real-world scientific problems in materials science and chemistry. You will work on projects involving one of these areas: enabling AI agents to reason over and orchestrate simulations, developing ML methods to accelerate atomistic simulations, and leveraging agentic simulations for applications in materials discovery.
What You'll Be Building
- Contribute to projects involving one of these areas: AI agents for simulations, ML models for atomistic simulations, and in silico materials discovery.
- Develop methods and workflows for in silico materials discovery that connect physics-based simulations, generative models, and agentic AI systems.
- Build intelligent pipelines where AI agents can design, launch, interpret, and refine simulations autonomously.
- Design new methods to accelerate simulations with ML-based surrogate models.
- Collaborate with computational scientists, machine learning experts, and platform engineers to integrate in silico
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