Co-op, AI for Protein Design

San Francisco, CAfull timeOn Site

H1B: no

Lila Sciences PhD-level Co-op at Lila Sciences contributes to applied ML research in protein engineering, including generative protein design and antibody engineering. The role involves analyzing biological datasets, prototyping workflows, and communicating results through code and presentations.

Responsibilities

This PhD-level co-op will join the Life Science AI team to contribute to applied ML research in protein engineering, including generative protein design, antibody engineering, developability, and wet-lab-informed model iteration. Working alongside Lila scientists and ML researchers, the co-op will explore generative and predictive models for protein sequence, structure, and function, analyze biological and experimental datasets to evaluate model outputs, and prototype workflows that connect model predictions, candidate prioritization, and wet-lab feedback. Results will be communicated through code, notebooks, written summaries, and presentations.
The ideal candidate is a currently enrolled PhD student in CS, ML, computational biology, bioengineering, biophysics, or a related field, with research experience in ML or protein engineering, strong Python skills, and experience with frameworks like PyTorch or JAX. Familiarity with protein language models, diffusion or flow-based models, antibody design, or active learning workflows is a plus.
What You'll Be Building
Research generative and predictive models for protein and antibody design
Analyze experimental datasets to evaluate model outputs and guide design decisions
Prototype workflows linking model predictions, candidate prioritization, and wet-lab feedback
Build datasets and benchmarks that support both domain-specific and general AI research models
Share results through code, notebooks, and presentations

Qualification

Currently enrolled PhD student in CSResearch experience in machine learningExperience with protein language modelsFamiliarity with antibody designPublicationsGuided by our core values of truth

Required

Currently enrolled PhD student in CS, ML, computational biology, bioengineering, biophysics, or a related field
Research experience in machine learning, computational biology, or protein engineering
Strong Python skills and experience with PyTorch, JAX, or similar frameworks
Experience working with biological sequence, structure, or assay data
Clear communication and comfort collaborating with cross-disciplinary teams

Preferred

Experience with protein language models, structure prediction, or generative design (diffusion or flow-based models)
Familiarity with antibody design, developability, or wet-lab validation concepts
Publications, preprints, or open-source work in ML for biology
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.
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 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.

Company

Lila Sciences

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