Co-Op, AI Nucleic Acid Design

Lila Sciences, Inc.; San Francisco (CA); On-site; USD 34,000 - 55,000; Full time

Job summary

Lila Sciences is seeking a motivated MS/PhD candidate to join the Nucleic Acid Design team for a 6-month co-op in San Francisco. You will lead a research project on RNA/DNA sequence design, building ML models and exploring generative approaches to predict sequence-function relationships.

You will work at the intersection of machine learning and biology, collaborating with experimental scientists to connect models to real data, and presenting findings for potential publications or talks.

Qualifications

• 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, with strong Python skills and 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 onsite in San Francisco.

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, for example by generating hypotheses, reasoning over experimental results or guiding design choices.
• Collaborate with experimental scientists to understand assays and to propose experiments that test new ideas.
• Present findings to the team and contribute to research write-ups, and where possible to external publications or presentations.

Skills

Python

ML models

Machine learning

Sequence data analysis

English communication

Education

MS/PhD student in ML/Computational Biology/CS

Tools

PyTorch

JAX

Job description

Lila Sciences is building scientific superintelligence by pairing large-scale automated experimentation with frontier machine learning. Within Lila, the Life Science AI (LSAI) function researches automated reasoning on biological data, combining state-of-the-art ML with breakthrough biology.

This co-op sits with the nucleic acid design group in LSAI, which builds models and design strategies for RNA and DNA sequences. You'll join our Nucleic Acid Design team for a 6-month co-op focused on open-ended research questions that could shape how Lila designs nucleic acid sequences in the future.

You'll work at the intersection of machine learning, sequence modeling and nucleic acid biology, on problems such as UTR design, regulatory element design, and using large reasoning models for scientific discovery. You'll own a defined research project with mentorship from ML scientists, and you'll work closely with experimental scientists to connect your models to real biological data.

The ideal candidate is curious, comfortable with open-ended problems, and excited to learn both the ML and biology behind sequence-to-function modeling.

What You'll Be Building

• 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, for example by generating hypotheses, reasoning over experimental results or guiding design choices.
• Collaborate with experimental scientists to understand assays and to propose experiments that test new ideas.
• Present findings to the team and contribute to research write-ups, and where possible to external publications or presentations.

What You'll Need to Succeed

• 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, with strong Python skills and 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 onsite in San Francisco.

Bonus Points For

• 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.

About LILA

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. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

Lila Sciences iscommitted to equal employment opportunityregardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

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