Scientist, Epitaxial Thin Film Synthesis at Lila Sciences - ScoutJobs - The AI-curated global job board
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Posted 18 hours ago

Scientist, Epitaxial Thin Film Synthesis

Lila Sciences

Requirements

Ph.D. in Physics, Materials Science, or Applied Physics, 4+ years experience in epitaxial thin film growth, Expertise in XRD-based structural analysis, Proficiency in surface characterization, Experience with cryogenic magneto-transport measurements, Experience with RHEED, Knowledge of vacuum science

Skills

Materials Science

About the role

Responsibilities

  • Grow single-crystal epitaxial thin films and heterostructures using sputtering, pulsed-laser deposition, or molecular beam epitaxy
  • Optimize deposition conditions to achieve atomically sharp interfaces and target crystal phases
  • Analyze XRD and AFM data
  • Design, fabricate, and measure electronic transport devices, including temperature-dependent resistivity, Hall effect, and magnetoresistance
  • Analyze magneto-transport data to extract physical parameters and identify emergent ground states
  • Maintain deposition and characterization equipment and troubleshoot vacuum systems
  • Collaborate with theorists and computational scientists to inform materials selection

Requirements

  • Ph.D. in Physics, Materials Science, Applied Physics, or a closely related field
  • Minimum of 4 years of hands-on experience growing epitaxial thin films
  • Demonstrated expertise in XRD-based structural analysis of crystalline thin films
  • Proficiency with surface characterization
  • Strong background in electronic and magneto-transport measurements at cryogenic temperatures
  • Experience operating RHEED for in-situ growth monitoring
  • Knowledge of vacuum science and ultra-high-vacuum system maintenance

Preferred Qualifications

  • Experience synthesizing thin film materials exhibiting correlated-electron phenomena
  • Publication record in peer-reviewed journals
  • Experience with combinatorial or high-throughput approaches to materials discovery
  • Experience with sputtering processes including DC, RF, and HiPIMS modes
  • Familiarity with lithographic patterning for transport device fabrication
  • Background in Bayesian optimization or machine-learning-guided experimental design

About the Company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously.

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Scientist, Epitaxial Thin Film Synthesis

Lila Sciences · Cambridge

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