From bits to atoms. Backed by Accel, Lightspeed and a16z.
About the role
Join a world-class team of scientists and engineers pushing the boundaries of materials research in a groundbreaking lab where AI and automation unlock discoveries at unprecedented speed and scale.
What they're looking for
- PhD in chemistry, physics, or materials science, with 5+ years of hands-on experience
- Deep expertise with thin-film synthesis methods such as sputtering, PLD, and MBE, with demonstrated experience and creativity across diverse chemistries
- Strong skills in structural and chemical characterization, particularly of thin films and materials with structures or compositions never before realized experimentally — including diffraction, microscopy, and spectroscopy
- Experience probing the optical, electronic, magnetic, thermal, and/or other properties of thin films
- Proven record of collaboration with computational groups, especially for high-throughput materials discovery
- Demonstrated commitment to laboratory safety and stewardship, with hands-on experience in hazardous chemistries
More about this role
We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
Join a world-class team of scientists and engineers pushing the boundaries of materials research in a groundbreaking lab where AI and automation unlock discoveries at unprecedented speed and scale.
As a Research Scientist in Thin Film Materials Discovery, you will lead thin-film synthesis efforts using advanced PVD platforms, building the experimental foundation for autonomous discovery loops. You will collaborate with computational and AI scientists, and partner with engineers designing next-generation automated laboratory infrastructure.
Develop synthesis strategies to realize novel thin-film materials predicted by AI
Determine and control crystal structures, defects, microstructures, and properties of previously unrealized compounds
Partner with AI and computation teams to build predictive models of materials...
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