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About the Role
This co-op opportunity is with the Life Science AI (LSAI) function, specifically within the nucleic acid design group. You will focus on open-ended research questions related to RNA and DNA sequence modeling and design, working at the intersection of machine learning, sequence modeling, and nucleic acid biology. The role involves owning a defined research project with mentorship and close collaboration with experimental scientists.
Responsibilities
- Lead a scoped research project in nucleic acid sequence modeling or design.
- Build ML models on RNA and DNA sequence-function data, including prototyping new methods for property prediction, generative design or candidate selection.
- Investigate model behavior and propose biological hypotheses about why sequences succeed or fail.
- Explore how large reasoning models can drive scientific discovery and sequence design.
- Collaborate with experimental scientists to understand assays and propose experiments.
- Present findings to the team and contribute to research write-ups, publications, or presentations.
Requirements
- Currently enrolled in an MS or PhD program in machine learning, computational biology, bioengineering, computer science, statistics or a related quantitative field.
- Hands-on experience building and training ML models.
- Strong Python skills.
- Experience with PyTorch, JAX or a similar framework.
- Coursework or research experience with biological sequence data (DNA or RNA).
- Curiosity about nucleic acid biology, such as RNA biology, gene regulation or sequence-to-function relationships.
- Available for a full-time, 6-month co-op term.
Skills
- Machine learning
- Sequence modeling
- Nucleic acid biology
- Python
- PyTorch
- JAX
- Biological sequence data (DNA or RNA)
- Sequence-to-function models
- Genomic language models
- MPRA
- Reporter assay
- Functional genomics data
- RNA secondary structure prediction
- UTR design
- Codon design
- Inverse design methods
- Generative modeling
- Active learning
- Bayesian optimization
- Wet-lab data
- Large language models
- Reasoning models
- AI agents
- LLM-based tools for scientific tasks
Location
- San Francisco
Work Type
- Full-time
- Co-op
- Onsite
Experience Level
- MS or PhD program enrollment
Education Level
- MS
- PhD
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.
- 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.
- Accelerates discovery at unprecedented speed, scale, and impact across medicine, materials, and energy.
- Guided by core values of truth, trust, curiosity, grit, and velocity.
- 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.