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Lila Sciences

AI-powered scientific discovery for medicines

Scientist 2/Senior Characterization Scientist - Condensed Matter

Physical SciencesConfirmed live in the last 24 hours
Full-timeCambridge, MA, USAIn-person

About the Job

Requirements

  • A 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.
  • Experience making measurements on materials and prototype devices.
  • Proficiency 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.

Responsibilities

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

Desired Qualifications

  • Familiarity with complementary characterization techniques such as X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), or spectroscopy.
  • Proficiency in Python or similar tools for data analysis and workflow automation.
  • Experience in custom instrumentation.
  • Broad exposure to different types of functional materials and applications.
  • Exposure to automated, high-throughput, or autonomous laboratory environments.
  • Background in multiple material classes, such as oxides, intermetallics, thin films, or two-dimensional materials.

About the Company

Lila Sciences

AI-powered scientific discovery for medicines

Lila.ai uses artificial intelligence to speed up scientific discovery in medicines and advanced materials. The system ingests large sets of scientific data, experimental results, and literature to identify patterns, generate hypotheses, and guide research programs. It differentiates itself by tackling deep scientific problems at scale and combining AI with domain expertise, rather than offering generic tools. The goal is to help humanity by delivering new medicines and materials that solve major biological and materials challenges through data-driven discovery.

Company size
501-1,000
Company stage
Series A
Total funding
$550M
Headquarters
Cambridge, MA
Founded
2024

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