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Research Scientist, Condensed Matter Theory

Periodic Labs· Science
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Menlo Park, CA; Montreal, Canada$225k - $325kFull-timePosted 11mo ago

About the role

Research Scientist role at Periodic Labs focusing on theoretical modeling to connect first-principles calculations and experiments in condensed matter physics, aiming to accelerate discovery of novel quantum materials.

Responsibilities

  • Develop and apply theoretical models to interpret experimental observations and guide materials discovery efforts
  • Bridge first-principles calculations (e.g., DFT) and experimental results to build predictive physical understanding
  • Collaborate with ML researchers to incorporate theoretical insights into machine learning models and inform training data strategies
  • Work with computational and experimental scientists to design experiments and validate theoretical predictions
  • Communicate theoretical findings clearly across disciplines and contribute to a shared scientific roadmap

Qualifications

  • PhD in condensed matter theory, with a focus on quantum materials
  • Deep expertise in relating theoretical models to real materials and experimental observables
  • Strong publication record demonstrating impactful, independent research
  • Ability to collaborate effectively across theory, computation, and experiment

Skills

Required:Theoretical modelingCollaboration across disciplinesScientific communication
Nice to have:First-principles calculations (DFT)Machine learning integrationSuperconductivity / magnetism modeling

Benefits

  • Not explicitly listed in the job description
Last updated Oct 7, 2026. Interested? Apply on the company site.

About Periodic Labs

From bits to atoms.

Periodic Labs is an artificial intelligence research company pioneering the next leap in scientific discovery. We operate at the intersection of machine learning and scientific experimentation under the thesis that that true understanding of the universe is only possible by interacting and experimenting on it.

artificial intelligencescientific discoverymachine learningscientific experimentation

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