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About the Role
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.
Responsibilities
- Contribute to projects involving AI agents for simulations, ML models for atomistic simulations, or in silico materials discovery.
- Develop methods and workflows for in silico materials discovery connecting physics-based simulations, generative models, and agentic AI systems.
- Build intelligent pipelines where AI agents can autonomously design, launch, interpret, and refine simulations.
- Design new methods to accelerate simulations using ML-based surrogate models.
- Collaborate with computational scientists, machine learning experts, and platform engineers to integrate in silico discovery pipelines into Lila's broader scientific superintelligence ecosystem.
Requirements
- Currently enrolled in an MS or PhD program in CS, Materials Science, Chemistry, Chemical Engineering, Physics, or a related field (exceptional BS candidates with research experience considered).
- Proficiency in Python, deep learning frameworks, and end-to-end workflow deployment.
- Evidence of applied ML research work in physical sciences including method development, model training and evaluation, and sound code practices.
- Strong communication and presentation skills, capable of conveying technical information clearly and thoroughly.
- Eager to work with highly skilled and dynamic teams in a fast-paced, entrepreneurial, and technical setting.
Skills
- Python
- Deep learning frameworks
- End-to-end workflow deployment
- Applied ML research in physical sciences
- Method development
- Model training and evaluation
- Code practices
- Communication
- Presentation skills
- ML interatomic potential development
- LLMs for materials science and chemistry
- Generative models for materials
- High-throughput computational materials discovery
- Open-source simulation or ML infrastructure and software contributions
- Materials science simulation codes
- Workflow orchestration frameworks
Location
- Remote
Work Type
- Full-time
Experience Level
- MS or PhD program enrollment
- Exceptional BS candidates with research experience
Education Level
- MS
- PhD
- BS
About the Company
- Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges.
- We believe science is the most inspiring frontier for AI.
- Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
- LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy.
- Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance.
Equal Opportunity
- Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.