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Platform Scientist I/II, Functional Materials Instrumentation

On-site
Lila SciencesCambridge, MA, US / MA, US5 hours agoWebsite
Fresh
Autonomous Science Platform

Compensation

$108,000-$170,000/yr
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Description

Your Impact at LILA

Lila Sciences is seeking a Platform Scientist I/II to advance functional materials innovation.

In this role, you will design and integrate custom instruments and specialized hardware, to fabricate, characterize, and test novel functional materials and devices.

This work sits at the intersection of hardware design, materials science, solid-state physics, and automated experimentation. Success means building lab capabilities that accelerate current technical programs and strengthen Lila's platform offering for future customers.

What You'll Be Building

  • Establish fabrication and measurement workflows for functional materials.
  • Specify, source, assemble, and validate custom synthesis and characterization systems, with an emphasis on optical characterization methods
  • Lead integration of instrumentation into autonomous lab and AI-driven experimental workflows.
  • Diagnose, iterate, and improve instrument designs based on experimental feedback.
  • Partner with computational, synthesis, and characterization teams to define which hardware capabilities to build next.

What You'll Need to Succeed

  • PhD or equivalent experience in applied physics, materials science, chemistry, or a related field.
  • Scientific domain of expertise in functional materials (semiconductor, photonics, superconducting materials etc.)
  • Expertise in solid state syntheses and characterization for functional materials
  • Proven ability to build and integrate hardware for novel and high throughput experimentation.
  • Ability to work in fast, data-driven, high-throughput R&D environments.

Bonus Points For

  • Proficient in writing software for controls, data collection, and analysis.
  • CAD, machining/3D printing, and rapid prototyping for custom hardware.
  • Knowledge of AI/ML-driven discovery workflows or autonomous lab platforms.
  • Experience with class 4 lasers

Stack

Machine Learning
Posted
Oct 6, 2026
Last seen
Oct 6, 2026
First seen
Oct 6, 2026

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