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Research Scientist I/II, Computational Organic Electronics

Lila Sciences·US·Cambridge, MA USA·mid
ml
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Your Impact at LILA Your role will involve applying computational methods and AI to accelerate the 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, or electronic devices. You will work at the intersection of physics-based simulation, AI/ML, and autonomous scientific workflows. The focus is on using computational insight to identify promising materials, explain structure-property relationships, guide optimization, and help agents reason over simulation and experimental data in scientifically grounded ways. This is a hands-on research role for someone who can connect deep organic electronics and computational materials expertise with practical impact for customer-facing scientific programs. You will collaborate with computational scientists, AI researchers, software engineers, and experimental teams to turn simulations, models, and scientific reasoning into actionable hypotheses and discovery workflows. What You'll Be Building Apply computational modeling and AI for materials discovery and design of organic semiconductors, photovoltaic materials, molecular and polymeric electronic materials, and organic electronic devices. Model charge transport, excited-state behavior, morphology-property relationships, and other fundamental mechanisms that influence organic electronic device 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. Partner with ML, software, and experimental teams on discovery workflows. Communicate physical ins

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