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Co-Op, Electron Microscopy

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

Compensation

Salary undisclosed
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Description

Your Impact at LILA

Lila Sciences is seeking a Co-Op, Electron Microscopy to join the Materials Science team within the Autonomous Science Platform. This co-op supports advanced SEM characterization workflows across powdered materials and thin films, working alongside synthesis, characterization, and ML scientists to turn physical experiments into high-quality data.

The work is hands-on and instrument-heavy: acquiring imaging and compositional data, refining methods, and iterating on protocols that feed Lila's materials discovery platform. It suits a PhD student who wants depth in microstructural analysis and sees how characterization data drives AI-guided materials research.

What You'll Be Building

  • Design and execute SEM-based characterization workflows across diverse chemistries and form factors
  • Operate electron microscopy instrumentation under the guidance of staff scientists
  • Partner with experimental scientists and engineers to optimize protocols and inform downstream analysis
  • Troubleshoot instrumentation and workflow issues that affect data quality
  • Capture imaging and analysis results in clear, reusable laboratory records
  • Follow safety and compliance standards for instrument and sample handling

What You'll Need to Succeed

  • Currently enrolled in a PhD in Materials Science, Physics, or a related field
  • Strong background in SEM-based microstructural analysis
  • Hands-on expertise with EDS, EBSD, and FIB (focused ion beam)
  • Experience characterizing powdered materials and thin films
  • Demonstrated ability to operate and troubleshoot advanced SEM systems
  • Strong organizational skills and attention to detail

Bonus Points For

  • Experience with image analysis tools such as ImageJ or Python-based pipelines
  • Familiarity with complementary techniques such as XRD or XRF
  • Interest in automation and integration of microscopy with AI workflows
  • Prior work characterizing nanoscale defects and interfaces

Stack

PythonMachine Learning
Posted
Oct 28, 2026
Last seen
Oct 28, 2026
First seen
Oct 28, 2026

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