Co-Op, Reaction Prediction & Benchmarking

The role

The co-op will develop and evaluate machine learning methods supporting small molecule design and synthesis. The person will pursue a focused research project in reaction prediction and benchmarking or molecular property prediction for medicinal chemistry optimization.

What you will do

• Plan and execute a Co-Op project in conjunction with the Molecular Intelligence team
• Build benchmarks to assess reaction prediction models and reaction plausibility
• Develop and fine-tune molecular property predictors using project-specific data
• Produce reproducible data and evaluation workflows, benchmark results, and research recommendations

Required qualifications

• Pursuing a graduate degree (MSc, PhD) in Chemistry, Computer Science, Physics, or similar

Nice to have

• Python (data processing, model training, and evaluation)
• Familiarity with cheminformatics libraries (RDKit or similar)
• Basic machine learning (supervised learning, model evaluation metrics)
• Familiarity with chemistry concepts through coursework or research experience
• experience with molecular property prediction, multi-task learning, self-supervised pre-training, or model fine-tuning
• familiarity with reaction data formats, reaction SMARTS, or reaction databases (e.g., Pistachio, Reaxys, SciFinder)
• background or interest in organic or medicinal chemistry

About the company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science.