Co-Op, AI Nucleic Acid Design

Preferred

• Experience with sequence-to-function models, genomic language models, or models trained on MPRA, reporter assay or other functional genomics data.
• Familiarity with RNA secondary structure prediction, UTR or codon design, or inverse design methods.
• Experience with generative modeling, active learning or Bayesian optimization.
• Exposure to wet-lab data or collaboration with experimental scientists.
• A research publication, preprint or open-source project in ML or computational biology.
• Experience using or building with large language or reasoning models, AI agents, or LLM-based tools for scientific tasks.
• Lila Sciences is building Scientific SuperintelligenceTM 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 FactoryTM 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. Learn more at www.lila.ai.