Co-op, Analytical Chemistry

Lila Sciences Lila Sciences · AI Frontier · Alewife, Cambridge, MA · Autonomous Science Platform

This role supports analytical chemistry tasks within a 'science factory' that uses AI-driven workflows to accelerate scientific discovery. The co-op will perform high-throughput analytical studies, spectroscopic and chromatographic analysis, and manage experimental data for AI-driven analysis, using Python for data processing. While the role contributes data to AI systems, it does not directly build or research AI models.

What you'd actually do

  1. Work hands-on with the synthesis team to drive high throughput analytical studies for small molecules
  2. Perform HTE spectroscopic and chromatographic analysis (IR, NMR, LC, MS) for reaction samples, and uncover mechanistic insights - both inline and offline characterization.
  3. Design and run experiments to accelerate catalytic discovery, collaborate with AI-driven workflows, enabling real-time learning cycle and push the limits of high-throughput chemical analysis.
  4. Perform instrument calibration, dilution and QC studies
  5. Digital log of experiment workflows, samples, reaction conditions, calibrations, and results, ensuring data integrity for AI-driven analysis. Use Python for data processing or instrument scripting.

Skills

Required

  • B.S. or M.S. in Analytical Chemistry or a related discipline
  • Hands-on experience in high-throughput analysis of small molecules
  • Comfort working with inert conditions and wide range of chemicals, adhering to EHS protocols and following detailed SOPs.
  • Effective written and verbal communication
  • ability to work in a fast-paced, multidisciplinary team

Nice to have

  • analytical method development for HT screenings of medicinal compounds
  • Basic proficiency in Python or another scripting language for data handling
  • Strong observational skills
  • attention to detail
  • willingness to ask questions and learn
  • Familiarity with automation platforms and high throughput experimentation
  • Background in pharma and analysis of medicinal compounds
  • Experience in troubleshooting and maintenance of analytical instruments

What the JD emphasized

  • AI-driven workflows
  • data integrity for AI-driven analysis