Research Scientist, Photonic Materials Discovery

Lila Sciences
Cambridge
Workplace: OnsiteFull timeUSD 176,000 - 304,000 annuallyFunction: Data Science & Machine LearningSkills: ["Communication","Collaboration","Problem-solving"]

Develop computational workflows to discover and optimize electro-optic and photonic materials, linking composition, defects, processing, and operating conditions to optical and electro-optic performance. Build and validate first-principles, atomistic, and multiscale (DFT/response-property) models, compare predictions to experiments, and create reproducible high-throughput simulations with uncertainty and provenance. Collaborate with experimental scientists, ML researchers, and software engineers on computational–experimental feedback loops and agentic discovery systems.

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Lila Sciences
Lila Sciences
3 days ago

Research Scientist, Photonic Materials Discovery

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Last checked: 12 hours agoStatus: Live

Job Summary

Develop computational workflows to discover and optimize electro-optic and photonic materials, linking composition, defects, processing, and operating conditions to optical and electro-optic performance. Build and validate first-principles, atomistic, and multiscale (DFT/response-property) models, compare predictions to experiments, and create reproducible high-throughput simulations with uncertainty and provenance. Collaborate with experimental scientists, ML researchers, and software engineers on computational–experimental feedback loops and agentic discovery systems.
Location: Cambridge
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Lead computational discovery efforts for electro-optic and integrated photonic materials.
  • •Develop and validate first-principles, atomistic, and multiscale workflows to predict electronic, vibrational, dielectric, optical, and electro-optic behavior.
  • •Interpret how composition, structure, defects, interfaces, strain, and temperature affect properties, including stability and performance tradeoffs.
  • •Create reproducible automated high-throughput workflows with data provenance, validation, convergence testing, and uncertainty assessment.
  • •Build agentic frameworks that orchestrate simulation codes, scientific databases, analysis tools, and surrogate models for iterative hypothesis refinement and failure recovery.

Pay and Benefits

Salary: USD 176,000 - 304,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionLife InsuranceDisability InsurancePaid ParentalCommuter BenefitsBike ShareMeal Allowance

Key Requirements

  • •PhD (or equivalent) in Physics, Materials Science, Chemistry, Electrical Engineering, or a related field.
  • •Strong background in computational condensed-matter physics/materials science and experience studying functional optical, dielectric, or electronic materials.
  • •Expertise in electronic-structure methods and calculating/interpreting dielectric, optical, vibrational, polarization, or related response properties.
  • •Working knowledge of crystallographic symmetry, lattice dynamics, light–matter interaction, and structure–property relationships.
  • •Experience with electronic-structure packages and reproducible HPC or cloud workflows, plus strong Python/scientific software skills.
Skills:CommunicationCollaborationProblem-solving
Tech Stack:PythonDFTHPCCloudFirst-principlesLattice dynamicsElectronic-structure methodsHigh-throughput simulationSurrogate modelsAgentic AIWorkflow orchestrationData provenanceUncertainty assessment

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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