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Salary: USD 176,000 - 304,000 / annual
Lila Sciences is seeking a Research Scientist to apply computational methods and AI to accelerate discovery and design of organic electronics materials. You will use first-principles modeling, atomistic simulations, scientific machine learning, and agentic AI systems to investigate structure-property relationships in organic and hybrid materials relevant to photovoltaics, semiconductors, optoelectronics, and electronic devices.
Your responsibilities include:
- Applying computational modeling and AI for materials discovery and design of organic semiconductors, photovoltaic materials, and molecular/polymeric electronic materials
- Modeling charge transport, excited-state behavior, morphology-property relationships, and mechanisms influencing organic electronic device performance
- Connecting simulation outputs to experimental observations and developing workflows that close the loop between computation and experiment
- Building predictive models from computational and experimental data to guide materials selection and optimization
- Analyzing simulation and experimental data to generate actionable materials hypotheses
- Partnering with ML, software, and experimental teams on discovery workflows
- Communicating physical insights, model limitations, and recommendations to cross-functional collaborators
You will work at the intersection of physics-based simulation, AI/ML, and autonomous scientific workflows, collaborating with computational scientists, AI researchers, software engineers, and experimental teams to turn simulations, models, and scientific reasoning into actionable hypotheses and discovery workflows.
Required qualifications:
- PhD or equivalent experience in Materials Science, Chemistry, Chemical Engineering, Mechanical Engineering, Physics, or related field
- Strong foundation in computational materials science and chemistry, including electronic structure methods and large-scale atomistic simulations
- Deep understanding of organic semiconductors, organic electronics, photovoltaics, optoelectronic materials, charge transport, or related device-relevant materials systems
- Experience applying first-principles, molecular simulations, or atomistic methods to materials discovery, optimization, or understanding
- Ability to connect molecular, morphological, and electronic structure features to device-relevant properties
- Strong Python programming and scientific computing skills
Bonus experience includes: organic photovoltaics, polymer electronics, molecular electronics, perovskite-organic interfaces; AI/ML applied to computational materials science; agentic AI systems and autonomous scientific workflows; integrating computational predictions with experimental characterization; charge transport modeling, excited-state calculations, morphology generation, multiscale simulations.
