Scientist Ii/senior Characterization Scientist, Condensed Matter

Lila Sciences Lila Sciences · AI Frontier · Alewife, Cambridge, MA · Autonomous Science Platform

The role focuses on developing and implementing advanced characterization workflows for magnetic and superconducting materials, integrating experimental science, robotics, and AI to guide materials discovery within an autonomous science platform. The scientist will design and execute high-throughput experiments, analyze data, and collaborate with ML scientists to build scalable workflows.

What you'd actually do

  1. Design, execute, and optimize characterization workflows for magnetic and superconducting materials using techniques such as magnetometry (VSM/SQUID), transport measurements, and AC susceptibility.
  2. Analyze and interpret complex datasets to extract materials properties including critical temperatures, field-dependent behavior, and magnetic ordering.
  3. Collaborate with experimentalists, systems engineers, and ML scientists to integrate characterization outputs into closed-loop autonomous experimental workflows.
  4. Develop and maintain protocols for sample preparation, instrument calibration, and quality control across diverse material types and form factors.
  5. Troubleshoot characterization workflows and instrumentation to sustain high-throughput operational performance.

Skills

Required

  • PhD in Materials Science, Physics, Chemistry, or a related field, with 1–5 years of postdoctoral or industry experience.
  • Demonstrated expertise in characterization of magnetic or superconducting materials, including proficiency with one or more of: VSM, SQUID magnetometry, PPMS, or equivalent platforms.
  • Strong understanding of the physics of magnetism, superconductivity, or related condensed matter phenomena.
  • Experienced in making measurements both on materials and protoype devices
  • Proficient in quantitative data analysis and interpretation of structure-property relationships in solid-state materials.
  • Effective written and verbal communication skills with a track record of cross-functional collaboration.

Nice to have

  • Familiarity with complementary characterization techniques such as XRD, TEM, SEM, or spectroscopy.
  • Proficiency in Python or similar tools for data analysis and workflow automation.
  • Experience in custom instrumentation
  • Wide breadth of exporuse to different types of functional materials and applications
  • Exposure to automated, high-throughput, or autonomous laboratory environments.
  • Background in multiple material classes (e.g., oxides, intermetallics, thin films, or 2D materials).
  • Comfort working in fast-paced, interdisciplinary research settings.

What the JD emphasized

  • autonomous science platform
  • high-throughput experiments
  • AI Science Factory

Other signals

  • autonomous science platform
  • high-throughput experiments
  • AI Science Factory