Platform Scientist, Soft Materials

Lila Sciences Lila Sciences · AI Frontier · One Charles Park, Cambridge, MA · Autonomous Science Platform

Seeking a Platform Scientist with a focus on soft materials to ideate, prototype, and transfer new experimental concepts for AI Science Factories. This role involves defining new approaches to formulation, structure-property relationships, and performance evaluation, and translating these concepts into scalable experimental workflows, custom apparatus, and software-enabled systems for autonomous research.

What you'd actually do

  1. Collaborate with diverse scientific teams to ideate new experimental strategies for soft and complex materials, including formulations, colloids, polymers, gels, and biological or hybrid systems
  2. Lead conceptual development of characterization and performance workflows leveraging techniques such as SAXS, SANS, rheology, and formulation performance assays
  3. Design, prototype, and validate custom apparatus, experimental methods, and software tools to realize these concepts
  4. Develop and refine workflows that connect structure, dynamics, and performance across multiple length and time scales
  5. Transfer successful prototypes into production-ready systems within Lila’s AI Science Factory platform, enabling autonomous experimentation

Skills

Required

  • MS or PhD in Materials Science, Chemistry, Chemical Engineering, Physics, or a related field, with a focus on soft or complex materials
  • Demonstrated experience collaborating across scientific disciplines to generate and refine experimental concepts
  • Hands-on experience with one or more of the following: SAXS, SANS, rheology, formulation performance or functional assays
  • Experience designing and implementing custom experimental workflows and/or scientific software
  • Strong programming skills (e.g., Python, C++, or similar) applied to data analysis, automation, or experiment control
  • Excellent communication skills and comfort operating in a fast-paced, exploratory R&D environment

Nice to have

  • Experience with lab automation, high-throughput experimentation, or instrument control software
  • Background in formulation science (e.g., consumer products, coatings, energy materials, bio-soft matter)
  • Experience linking scattering, rheological, and performance data to predictive or ML-driven models
  • Familiarity with prototyping tools such as 3D printing, machining, microfluidics, or custom sample environments
  • Industry or national lab experience working on soft materials or complex fluids