SEM Characterization Co-Op for Materials Discovery

Lila Sciences, Inc.; Cambridge (MA); On-site; USD 30,000 - 36,000; Part time

Job summary

Lila Sciences, Inc. is seeking a Co-Op, Electron Microscopy to join the Materials Science team in Cambridge, MA. You will support SEM characterization workflows for powdered materials and thin films, collaborating with synthesis, characterization, and ML scientists to convert experiments into high-quality data.

The role is hands-on, instrument-heavy, and suitable for a PhD student seeking depth in microstructural analysis and AI-driven materials research.

Qualifications

• PhD enrollment in Materials Science, Physics, or related field.
• Strong background in SEM-based microstructural analysis.
• Hands-on expertise with EDS, EBSD, and FIB.
• Experience characterizing powdered materials and thin films.
• Ability to operate and troubleshoot advanced SEM systems.
• Strong organizational skills and attention to detail.

Responsibilities

• 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.

Skills

SEM analysis expertise

Data organization

Troubleshooting instrumentation

Education

PhD in Materials Science/Physics

Tools

EDS

EBSD

FIB

SEM systems

Job description

Lila Sciences, Inc. is seeking a Co-Op, Electron Microscopy to join the Materials Science team in Cambridge, MA. You will support SEM characterization workflows for powdered materials and thin films, collaborating with synthesis, characterization, and ML scientists to convert experiments into high-quality data.

The role is hands-on, instrument-heavy, and suitable for a PhD student seeking depth in microstructural analysis and AI-driven materials research.