Research Scientist, Thin Films (AI)

TL;DR

Research Scientist (AI/Materials Science): Leading thin-film synthesis and experimental materials discovery within an autonomous, AI-driven laboratory environment with an accent on PVD platforms and high-throughput characterization. Focus on integrating experimental growth strategies with predictive AI models to accelerate the development of novel physical compounds.

Location: On-site in Menlo Park, California

Company

An AI and physical sciences startup building state-of-the-art models for novel scientific discoveries through autonomous laboratory infrastructure.

What you will do

• Develop synthesis strategies to realize novel thin-film materials predicted by AI models.
• Control and characterize crystal structures, defects, and properties of previously unrealized compounds.
• Partner with AI and computation teams to build physics- and chemistry-grounded predictive growth models.
• Collaborate with engineers to design, test, and deploy automated growth and characterization hardware.
• Maintain high laboratory safety standards and stewardship for hazardous chemical processes.

Requirements

• PhD in chemistry, physics, or materials science.
• 5+ years of hands-on experience in thin-film synthesis (e.g., sputtering, PLD, MBE).
• Expertise in structural and chemical characterization techniques such as diffraction, microscopy, and spectroscopy.
• Proven record of successful collaboration with computational or high-throughput research groups.
• Strong background in probing optical, electronic, magnetic, or thermal film properties.
• Track record of impactful research through top-tier publications or inventions.

Nice to have

• Experience working in national user facilities like synchrotrons or neutron sources.
• Development of novel experimental synthesis or characterization techniques.
• Proficiency in managing large experimental datasets and analysis pipelines.
• Experience with laboratory automation and scripting.

Culture & Benefits

• Well-funded startup environment focused on rapid growth and scientific impact.
• Highly collaborative team of scientists and engineers building next-generation infrastructure.
• Ownership-driven culture with minimal bureaucracy.
• Commitment to learning new scientific tools and solving complex problems without boundaries.