Co-op, AI for Protein Design
- LocationSan Francisco, CA USA
- Work typeNot stated
- Posted6 November 2026
- SourceLila Sciences's careers page (Greenhouse)
Live checkFirst seen 1 h ago; still listed on Lila Sciences's careers page 1 h ago.
At a glance
- EducationPhD
- Skills and toolsPython, PyTorch, Machine learning
Read from the ad by RoleFinder rules; the description is the source.
Back from the application? Add your CV and RoleFinder scores your fit for this role, then ranks your best 12 open roles where you want to work, each with a one-line reason.
Check my fitAbout the role
Your Impact at LILA
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.
The role advances our domain-specific protein design models while the data, methods, and evaluation tools built along the way also strengthen our general AI research model, directly supporting Lila’s mission of combining automated data generation with scientific superintelligence.
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
What You'll Need to Succeed
- 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
Bonus Points For
- 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
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.
We’re All In
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.
Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy .
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Are you a fit for this role?
Add your CV and RoleFinder scores your fit for Co-op, AI for Protein Design first, with a one-line reason. Then it ranks the open roles where you want to work, plus remote ones, shows your best 12, and emails you new matches once a week. The file is read once by AI and not kept; employers never see it.
Sign in with Google or email to start. How we handle your CV