About the role#
This co-op role focuses on developing autonomous scanning electron microscopy (SEM) workflows to improve the consistency and throughput of materials characterization. You will work at the intersection of materials science, image analysis, and laboratory automation to transform SEM from a manual tool into a system capable of navigating samples and making independent acquisition decisions. This is a hands-on position requiring collaboration with ML scientists and experimental researchers to define operational guardrails and instrument control requirements.
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.
What you'll need#
- Current pursuit or completion of 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 documented workflow logic.
Location & details#
- Location: Cambridge, Massachusetts
- Work modality: On-site
- Term: Rolling
- Status: Full-time, paid
About Lila Sciences
Lila Sciences operates as a scientific superintelligence platform and autonomous lab. The company focuses on life, chemistry, and materials science. It applies artificial intelligence to the scientific method to assist with research in human health and sustainability. Founded in 2023, the organization maintains its headquarters in Cambridge, Massachusetts. It currently employs 474 people.
How to get in at Lila Sciences
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