ML Scientist Co-Op

Responsibilities

• Contribute to ML research projects focused on protein engineering, antibody design, and related biomolecule design problems
• Explore generative and predictive modeling approaches for protein sequence, structure, function, and developability
• Work with scientists and ML researchers to translate biological design goals into tractable computational problems
• Analyze biological and experimental datasets to identify patterns, evaluate model outputs, and guide design decisions
• Prototype workflows that connect model predictions, candidate prioritization, and wet-lab feedback
• Communicate results clearly through code, notebooks, written summaries, and presentations

Requirements

• Currently enrolled as a PhD student in Computer Science, Machine Learning, Computational Biology, Bioengineering, Biophysics, or a related quantitative field
• Research experience in machine learning, computational biology, protein engineering, or a closely related area
• Strong programming skills in Python
• Experience with modern ML frameworks such as PyTorch or JAX
• Ability to work with biological sequence, structure, assay, or other scientific datasets
• Clear communication skills and comfort working in a collaborative, cross-disciplinary research environment

Preferred Qualifications

• Experience with protein language models, structure prediction, generative protein design, diffusion, or flow-based models
• Familiarity with protein structure, biophysics, developability, affinity maturation, or wet-lab validation concepts
• Publications, preprints, open-source work, or research projects in ML for biology or AI for Science
• Experience building active learning, model evaluation, or data analysis workflows for scientific discovery

About the Company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges by combining advanced AI models with proprietary AI Science Factory™ instruments to accelerate discovery across medicine, materials, and energy.