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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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Lila Sciences · Cambridge
