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Scientist II/Senior Characterization Scientist, Condensed Matter

External
lilasciences logoLilasciences · Cambridge, UK
$128K–$198K/yrFull-timeOn-site3w ago
ComplianceCross-functional CollaborationData AnalysisMachine LearningMovePython
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Benefits

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.Expected Base Salary Range$128,000 - $198,000 USDAbout LILALila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.We're All InLila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.Information you provide duringDental insuranceVision insuranceFlexible scheduleEquity / stock optionsPerformance bonusParental leave

Additional Information

Your Impact at LILA As a Scientist II/Senior Scientist on the PS Experiment team at Lila Sciences, you will drive the development and implementation of advanced characterization workflows for magnetic and superconducting materials. You will be a core contributor to Lila's autonomous science platform, designing and executing high-throughput experiments that yield critical structural, magnetic, and transport data to guide materials discovery. Working at the intersection of experimental science, robotics, and AI, you will collaborate with experimentalists, systems engineers, and machine learning scientists to build scalable characterization workflows that accelerate the path to scientific superintelligence in superconductivity and magnetism. What You'll Be Building 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 ML 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. What You'll Need to Succeed 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. Bonus Points For 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.


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