About the role#
Lila Sciences is seeking a Co-Op to join the Materials Science team within the Autonomous Science Platform. This role focuses on developing autonomous scanning electron microscopy (SEM) workflows to improve characterization consistency and throughput. You will work at the intersection of materials characterization, image analysis, and autonomous laboratory systems, helping to transform SEM from a manual tool into a system capable of navigating samples and making independent acquisition decisions.
What you'll do#
- Support the development of autonomous SEM workflows using vendor APIs.
- Test navigation logic for locating particles, surfaces, and regions of interest.
- Evaluate image quality based on focus, contrast, feature visibility, and sampling value.
- Support experiments that connect imaging decisions to downstream analysis and machine learning training needs.
- Document acquisition behavior, edge cases, and failure modes across various sample types.
- Collaborate with ML scientists and experimentalists to define practical guardrails for autonomous operation.
What you'll need#
- Currently pursuing or have completed a PhD in Materials Science, Chemistry, Chemical Engineering, Physics, Applied Physics, Computer Science, or a related technical field.
- Experience building automated scientific or laboratory workflows using Python.
- Deep understanding of electron optics, electron-beam interaction with matter, column alignments, stigmation correction, and source dynamics.
- Familiarity with MCP servers, LLM-enabled workflows, or agentic control of scientific instruments.
- Experience with closed-loop learning, active learning, Bayesian optimization, or reward-driven experimental workflows.
- Ability to translate expert instrument operations into clear, testable, and well-documented workflow logic.
Location & details#
- Location: Cambridge, Massachusetts.
- Modality: On-site.
- Employment: Full-time co-op position.
- Compensation: Paid.
