Lila Sciences is looking to build the next generation of biological models that will be foundational to Lilaâs autonomous discovery loop, aiming to improve state-of-the-art models for biomolecule (DNA, RNA, and proteins) design and enable scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before.
Requirements
- PhD or equivalent research experience in ML models for biological domains.
- Experience with training and using state-of-the-art biomolecule design models (AlphaFold, Evo2, ESM, etc).
- Experience designing and running experiments to improve model performance
- Strong coding skills and ML framework(PyTorch, JAX, etc) expertise.
- Publications in ML for biology at top research venues.
- Experience with building design-build-test loops (DBTL) for biomolecular design
- Experience with large language models or reinforcement learning.
Responsibilities
- Pursue a research agenda to improve state-of-the-art models for biomolecule (DNA, RNA, and proteins) design.
- Scientific reinforcement learning environments to improve model performance.
- Autonomous pipelines that integrate experimental feedback with in silico predictions.
- Train, test, and deploy models for experimentation.
- Work closely with researchers and engineers to train, test, and deploy models for experimentation.
Other
- Are passionate about the impact of AI for science.
