Lila Sciences
Biotech
Scientist,EpitaxialThinFilmSynthesis
Neural analysis suggests this role is
optimal for Senior candidates.
“Scientist, Epitaxial Thin Film Synthesis at Lila Sciences. Skills: Materials growth, Structural characterization, Electronic transport. Lead synthesis of epitaxial thin films. Contribute to discovery of quantum materials”
What You'll Achieve.
Accelerate discovery of novel materials
Industry & Context.
Troubleshoot hardware; Troubleshoot vacuum systems
What They're Looking For.
Must Have
PhD in Physics, Materials Science PhD, Applied Physics PhD, 4 years hands-on experience, Epitaxial thin films growing, XRD-based structural analysis, Surface characterization proficiency, Electronic transport measurements, Magneto-transport measurements, Cryogenic temperatures experience, RHEED operation experience, Vacuum science knowledge, UHV system maintenance
Nice to Have
Thin film materials synthesis, Correlated-electron phenomena experience, Magnetism experience, Spin-orbit coupling experience, Low-carrier-density transport anomalies, Publication record, Combinatorial approaches experience, High-throughput approaches experience, Sputtering processes experience, DC sputtering modes, RF sputtering modes, HiPIMS sputtering modes, Lithographic patterning familiarity, Bayesian optimization background, Machine-learning-guided design background
What You'll Do.
Lead synthesis of epitaxial thin films
Contribute to discovery of quantum materials
Design growth protocols
Design characterization protocols
Grow single-crystal epitaxial films
Grow heterostructures
Optimize deposition conditions
Achieve atomically sharp interfaces
Achieve target crystal phases
Design electronic transport devices
Fabricate electronic transport devices
Measure electronic transport devices
Analyze magneto-transport data
Extract physical parameters
Identify emergent ground states
Maintain deposition hardware
Maintain characterization hardware
Troubleshoot hardware
Troubleshoot vacuum systems
Collaborate with theorists
Collaborate with computational scientists
How You'll Work.
Team & Collaboration
Experimentalists; Systems engineers; Machine learning scientists; Theorists; Computational scientists
Full Job Description
Your Impact at LILA As an epitaxial thin film scientist on the Materials Science team at Lila Sciences, you will serve as the lead for synthesis of high-quality epitaxial thin films, contributing to the discovery of novel quantum materials with emergent electronic and magnetic properties. Your domain expertise at the intersection of materials growth, structural characterization, and electronic transport will translate into the method design and automated workflow to enable high throughput experimentation that Lila's autonomous science platform learns from. This work contributes to Lila's materials science programs focused on the predictive design of novel material families and compounds with novel functional properties. You will design growth and characterization protocols that shape how the platform interrogates new material systems, and your experimental outputs feed directly into the next round of campaigns. You will partner with experimentalists, systems engineers, and machine learning scientists, providing the functional-properties knowledge that keeps closed-loop campaigns scientifically grounded and accelerating toward next-generation materials systems. What You'll Be Building Grow single-crystal epitaxial thin films and heterostructures using epitaxial deposition methods (sputtering, pulsed-laser deposition, molecular beam epitaxy). Optimize deposition conditions (substrate temperature, flux ratios, growth rate) 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; troubleshoot hardware and vacuum systems. Collaborate with theorists and computational scientists to inform materials selection and interpret experimental results. What Yo
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