Research Scientist, Computational Condensed Matter Physics

Lila Sciences
Cambridge
Workplace: OnsiteFull timeUSD 176,000 - 304,000 annuallyFunction: Data Science & Machine LearningEducation: phdSkills: ["Communication","Collaboration","Scientific reasoning"]

Apply computational condensed matter physics and electronic-structure expertise to accelerate materials discovery and optimization. Build predictive models from computational and experimental data, run first-principles and atomistic simulations (including electronic structure and phonon calculations), and develop workflows that close the loop between computation and experiment. Collaborate across physics, AI/ML, software engineering, and experimental teams to generate scientifically grounded hypotheses for superconductors, quantum materials, and electronic devices.

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Lila Sciences
Lila Sciences
1 month ago

Research Scientist, Computational Condensed Matter Physics

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Last checked: 3 hours agoStatus: Live

Job Summary

Apply computational condensed matter physics and electronic-structure expertise to accelerate materials discovery and optimization. Build predictive models from computational and experimental data, run first-principles and atomistic simulations (including electronic structure and phonon calculations), and develop workflows that close the loop between computation and experiment. Collaborate across physics, AI/ML, software engineering, and experimental teams to generate scientifically grounded hypotheses for superconductors, quantum materials, and electronic devices.
Location: Cambridge
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Apply computational condensed matter physics to materials discovery and optimization.
  • •Use computational physics methods (electronic structure and phonon calculations) to study quantum materials, superconductors, and electronic devices.
  • •Connect simulation outputs to experimental observations and develop closed-loop computation–experiment workflows.
  • •Build predictive models from computational and experimental data to guide materials selection and optimization.
  • •Analyze simulation and experimental data to generate actionable materials hypotheses and communicate physical insights and model limitations.

Pay and Benefits

Salary: USD 176,000 - 304,000 annually
Perks:Health InsuranceDentalVisionLife InsuranceDisability InsurancePaid ParentalLearning BudgetCommuter Benefits

Key Requirements

  • •PhD (or equivalent) in Physics, Materials Science, Chemistry, Applied Mathematics, or a related field.
  • •Strong foundation in computational condensed matter physics, electronic structure, or atomistic simulation.
  • •Deep understanding of electronic-structure theory (e.g., quantum chemistry, DFT, beyond-DFT) for electronic, magnetic, or quantum materials.
  • •Experience applying first-principles or atomistic methods to materials discovery, optimization, or understanding.
  • •Strong programming skills in Python and scientific computing workflows.
Experience:Computational materials scienceQuantum materialsSuperconductorsScientific machine learning
Education:PhD / Doctorate
Skills:CommunicationCollaborationScientific reasoning
Languages:English
Tech Stack:PythonDFTElectronic structurePhonon calculationsFirst-principles modelingAtomistic simulationAI/ML

Company Brief

Lila Sciences
Develops AI-driven platforms to accelerate drug discovery and biological research by integrating machine learning with chemical and biological data to predict molecular properties, streamline candidate selection, and enable faster therapeutic development.
Industry: Biotech
Company Size: Small (11 to 50 employees)
Growth: Early Stage Startup
Funding: Seed
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