Co-Op, Electron Microscopy
Lila Sciences
- Location
- Cambridge, MA
- Job type
- Internship
- Posted
- Oct 28
- 2 days ago
Career path
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About the company
Lila Sciences
Internet · 2 to 10 employees
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
What you'll do
- 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 need
- 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
- Experience with image analysis tools such as ImageJ or Python-based pipelines (preferred)
- Familiarity with complementary techniques such as XRD or XRF (preferred)
Key skills
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