Research Scientist I/II, Computational Organic Electronics

Lila Sciences; Cambridge (MA); On-site; USD 176,000 - 304,000; Full time

Job summary

Lila Sciences in Cambridge, MA, seeks a researcher to apply computational methods and AI to accelerate discovery and design of organic electronics materials. You will work at the intersection of physics-based simulation, AI/ML, and autonomous scientific workflows to identify promising materials and guide optimization.

You will collaborate with computational scientists, AI researchers, software engineers, and experimental teams to turn simulations into actionable hypotheses and discovery

Qualifications

• PhD or equivalent experience in materials science, chemistry, chemical engineering, physics, or related field.
• Strong foundation in computational materials science and chemistry, including electronic structure methods and large-scale atomistic simulations.
• Experience applying AI/ML to computational materials science, molecular simulations, or related physics-based simulations.
• Ability to connect molecular, morphological, and electronic structure features to device-relevant properties.

Responsibilities

• Apply computational modeling and AI for materials discovery and design of organic semiconductors, photovoltaic materials, and related organic electronic materials.
• Model charge transport, excited-state behavior, morphology-property relationships, and device-relevant mechanisms.
• 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 insights, model limitations, and recommendations to collaborators.

Skills

Python programming

Computational materials science

Molecular simulations

First-principles methods

AI/ML experience

Education

PhD in Materials Science, Chemistry, Chemical Engineering, Physics, or related field

Tools

DFT

Molecular dynamics

ML frameworks (TensorFlow/PyTorch)

Job description

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 insights, model limitations, and recommendations to collaborators.

What You’ll Need To Succeed

• 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 understanding of organic semiconductors, organic electronics, photovoltaics, optoelectronic materials, charge transport, or related device-relevant materials systems.
• Experience applying first-principles, molecular simulations, or general atomistic methods to materials discovery, optimization, or understanding.
• Ability to connect molecular, morphological, and electronic structure features to device-relevant properties.
• Strong programming skills in Python and scientific computing workflows.

Bonus Points For

• Experience studying organic photovoltaics, organic semiconductors, polymer electronics, molecular electronics, perovskite-organic interfaces, or related materials systems.
• Experience applying AI/ML to computational materials science, molecular simulations, or other physics-based simulations.
• Strong familiarity with agentic AI systems, autonomous scientific workflows, or simulation-aware agents.
• Experience integrating computational predictions with experimental characterization, device measurements, or closed-loop optimization workflows.
• Familiarity with charge transport modeling, excited-state calculations, morphology generation, coarse-graining, and/or multiscale and multiphysics simulations.
• Ability to communicate physical insight, uncertainty, and model limitations to cross-functional collaborators.

Compensation

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range: $176,000 USD - $304,000 USD

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you’d love to work in, even if you don’t meet every qualification listed above, we encourage you to apply.

We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect to it.