Research Scientist I/II, Computational Organic Electronics

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

Apply computational modeling and AI to accelerate the discovery and design of organic electronic materials. Use first-principles modeling, atomistic simulations, scientific machine learning, and agentic AI workflows to study structure–property relationships, predict charge transport and excited-state behavior, and connect simulation outputs to experimental observations. Collaborate across computational science, AI, software engineering, and experimental teams to build closed-loop materials discovery and optimization workflows.

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Lila Sciences
Lila Sciences
3 days ago

Research Scientist I/II, Computational Organic Electronics

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Last checked: 22 hours agoStatus: Live

Job Summary

Apply computational modeling and AI to accelerate the discovery and design of organic electronic materials. Use first-principles modeling, atomistic simulations, scientific machine learning, and agentic AI workflows to study structure–property relationships, predict charge transport and excited-state behavior, and connect simulation outputs to experimental observations. Collaborate across computational science, AI, software engineering, and experimental teams to build closed-loop materials discovery and optimization workflows.
Location: Cambridge
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Entry level

Key Responsibilities

  • •Apply computational modeling and AI for materials discovery and design of organic semiconductors, photovoltaic materials, electronic polymers, and devices.
  • •Model charge transport, excited-state behavior, morphology–property relationships, and other mechanisms driving organic electronic performance.
  • •Connect simulation outputs to experimental observations and develop workflows that close the loop between computation and experiment.
  • •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, limitations, and recommendations to collaborators.

Pay and Benefits

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

Key Requirements

  • •PhD (or equivalent experience) in Materials Science, Chemistry, Chemical Engineering, Mechanical Engineering, Physics, or a related field.
  • •Strong foundation in computational materials science and chemistry, including electronic structure methods and large-scale atomistic simulations.
  • •Deep knowledge of organic semiconductors/electronics, photovoltaics, optoelectronic materials, and device-relevant charge-transport mechanisms.
  • •Experience with first-principles, molecular simulations, or other atomistic methods for materials discovery, optimization, or understanding.
  • •Strong programming skills in Python and ability to connect molecular/morphological/electronic features to device-relevant properties.
Experience:Computational materials scienceOrganic electronicsPhotovoltaicsMolecular simulationsAI/ML
Education:PhD / Doctorate
Skills:CollaborationScientific communicationScientific reasoningProblem-solvingTeamwork
Tech Stack:Python

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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