Computational Materials Scientist — Quantum Materials & Discovery

Lila Sciences; Cambridge (MA); On-site; USD 176,000 - 304,000; Full time

Benefits offered by this job

Medical, dental, vision

Equity

Commuter benefits

Company lunch program

Job summary

Lila Sciences in Cambridge is seeking a PhD-level physicist to apply computational condensed matter physics and electronic structure expertise to accelerate materials discovery and optimization. You will work at the intersection of physics-based simulation, AI/ML, and autonomous scientific workflows, building predictive models and discovery pipelines with collaborators across ML, software, and experiments.

The role includes a full-time arrangement with a competitive USD salary and equity.

Qualifications

• PhD or equivalent in Physics, Materials Science, Chemistry, or applied math.
• Strong foundation in computational condensed matter physics or atomistic simulation.
• Deep understanding of electronic-structure theory (DFT, beyond-DFT) and their application to materials.
• Experience with first-principles methods for materials discovery and optimization.
• Familiarity with superconductors, quantum materials, or device-relevant systems.
• Strong Python skills and scientific computing workflows.

Responsibilities

• Apply computational condensed matter methods to materials discovery and optimization.
• Develop predictive models from computational and experimental data to guide materials selection.
• Connect simulation outputs to experimental observations and develop discovery workflows.
• Collaborate with ML, software, and experimental teams on discovery workflows.
• Communicate physical insights, model limitations, and recommendations to collaborators.

Skills

Python programming

Education

PhD or equivalent in Physics/Materials Science/ Chemistry /Applied Mathematics

Tools

DFT

Job description

Lila Sciences in Cambridge is seeking a PhD-level physicist to apply computational condensed matter physics and electronic structure expertise to accelerate materials discovery and optimization. You will work at the intersection of physics-based simulation, AI/ML, and autonomous scientific workflows, building predictive models and discovery pipelines with collaborators across ML, software, and experiments.

The role includes a full-time arrangement with a competitive USD salary and equity.