---
title: 'Research Scientist I/II, Computational Organic Electronics at Lila Sciences'
canonical: 'https://feeny.ai/job/research-scientist-i-ii-computational-organic-electronics-lila-sciences-mh2tq43ahp5d'
type: 'job'
last_seen: '2026-09-04'
---

# Research Scientist I/II, Computational Organic Electronics at Lila Sciences

- **Company:** Lila Sciences
- **Location:** Cambridge, MA
- **Compensation:** $176k–$304k
- **Posted:** 2026-08-21
- **Last confirmed live:** 2026-09-04
- **Apply:** https://job-boards.greenhouse.io/lilasciences/jobs/4376824009

## 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—$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.

Information you provide during your application process will be handled in accordance with our [Candidate Privacy Policy](https://www.lila.ai/candidate-privacy-policy-notice).

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 thereto.

## About Lila Sciences

## Company Overview
- **One-liner**: Lila Sciences is building the world’s first Scientific Superintelligence platform and autonomous lab, using AI to autonomously generate hypotheses, design and run experiments, and learn from results in real time across life sciences, chemistry, materials, energy, and defense.
- **Entity Type**: Private (Privately Held) – Series A, Seed, and Grant funding rounds
- **Headquarters**: Cambridge, Massachusetts, United States
- **Founded**: Not publicly available (first funding round was Seed in March 2025)
- **Founders**: Not publicly available (founded within Flagship Pioneering’s ecosystem)

## Core Business
- **Primary industry**: AI-powered scientific discovery and autonomous laboratory platforms
- **Target customers**: B2B – research organizations, biotech, pharmaceutical, energy, materials, aerospace, and defense companies
- **Mission**: “Scientific Superintelligence to solve humankind’s greatest challenges” – accelerating discovery across medicine, materials, energy, and defense

## Products & Services
- **LILA Platform (Scientific Superintelligence)**: An AI model and operating system that autonomously executes the entire scientific method – generating hypotheses, designing experiments, running them in physical labs, and learning from results in real time.
- **AI Science Factory™ Instruments**: Proprietary hardware and robotics that serve as the “body” of the platform, enabling automated experimentation at scale.
- **Domain-specific applications**: Tailored solutions for biotech (drug discovery, protein engineering), therapeutics (mRNA, antibodies, cell therapies), energy & environment (clean fuels, catalysis, critical minerals), advanced materials, chemicals, aerospace & defense, and oil & gas.

## Market Standing
- **Valuation**: Not disclosed
- **Key Metric**: Total funding – USD $550.7M (as of LinkedIn data)
  - Seed Round (March 2025): $200M led by Flagship Pioneering
  - Series A (September 2025): $235M led by Braidwell and Collective Global Management
  - Series A (November 2025): $115M led by NVentures (NVIDIA)
  - Grant (January 2026): $671,400 led by ARIA
- **Notable Investors/Partners**: Flagship Pioneering, NVIDIA (NVentures), Braidwell, Collective Global Management, ARIA
- **Growth Signals**: Named #25 on the 2026 CNBC Disruptor 50 List; headcount of 308 employees (monthly growth +10.6%); 122 active job postings; operates in 6 countries (US, UK, Canada, Poland, Spain, Germany)

## Competitive Advantages
- **Proprietary AI model** that consistently outperforms other models across scientific domains in complex analysis and reasoning.
- **Autonomous physical labs** that close the loop between AI hypothesis generation and real-world experimentation.
- **“Team of Teams” operating model** enabling startup speed at scale while maintaining radical transparency and high trust.
- **General platform approach** (inspired by Rich Sutton’s “Bitter Lesson”) rather than narrow domain-specific tools, allowing broad applicability.

## Strategic Focus
- Accelerating discovery across medicine, materials, energy, and defense
- Scaling the autonomous science platform to more industries and use cases
- Building “Scientific Superintelligence” that can tackle humanity’s greatest challenges
- Continued investment in AI research, robotics, and lab automation

## Why Work Here
- **Culture**: Emphasizes velocity, trust, curiosity, truth, and grit. “Think freely, prove precisely.” A high-trust, mission-driven environment where scientists and engineers work side by side.
- **Remote/Hybrid/Office**: Roles are listed in Cambridge, MA; San Francisco, CA; and London, UK. Physical lab presence suggests significant on-site work, but some roles may offer flexibility. Policy not explicitly stated.
- **Notable perks/engineering culture**: Opportunity to work at the frontier of AI and scientific discovery; collaboration with world-renowned experts; access to cutting-edge robotics and AI infrastructure; strong emphasis on learning and teaching (“generous teachers and eager learners”).

## Sources
1. [lila.ai](https://www.lila.ai/)
2. [lila.ai/about](https://www.lila.ai/about)
3. [lila.ai/open-roles](https://www.lila.ai/open-roles)
4. [LinkedIn - Lila Sciences](https://www.linkedin.com/company/lila-sciences)
5. [Greenhouse Job Board](https://job-boards.greenhouse.io/lilasciences/jobs/4246302009)

## Other roles at Lila Sciences

- [Data Scientist II / Senior Data Scientist, Life Sciences](https://feeny.ai/job/data-scientist-ii-senior-data-scientist-life-sciences-lila-sciences-cambridge-wvrt5y3pkr50) — Cambridge, MA
- [Senior Data Engineer, Bioinformatics, Cheminformatics, Materials](https://feeny.ai/job/senior-data-engineer-bioinformatics-cheminformatics-materials-lila-sciences-san-kp5d4nbn38vz) — San Francisco, CA
- [Associate Director, App](https://feeny.ai/job/associate-director-app-lila-sciences-cambridge-46qgd5hp866e) — Cambridge, MA / San Francisco, CA
- [Maintenance Engineering Technician II](https://feeny.ai/job/maintenance-engineering-technician-ii-lila-sciences-cambridge-qgp4st6zk9gw) — Cambridge, MA
- [Research Scientist, Photonic Materials Discovery](https://feeny.ai/job/research-scientist-photonic-materials-discovery-lila-sciences-cambridge-m87b6zgatgmg) — Cambridge, MA
- [Associate Engineer/ Engineer I, Formulations and Characterization](https://feeny.ai/job/associate-engineer-engineer-i-formulations-and-characterization-lila-sciences-6dy4t3wbbqar) — Cambridge, MA
- [Senior Manager, Scientific Discovery Capacity Planning](https://feeny.ai/job/senior-manager-scientific-discovery-capacity-planning-lila-sciences-cambridge-c1tjq0yzrj9f) — Cambridge, MA
- [Finance Business Partner, AI & Software](https://feeny.ai/job/finance-business-partner-ai-software-lila-sciences-cambridge-dme1cxf7yazg) — Cambridge, MA
- [Associate Director / Director, Strategic Finance](https://feeny.ai/job/associate-director-director-strategic-finance-lila-sciences-cambridge-fp5gxvaqvt2k) — Cambridge, MA
- [Scientist II/Senior Melt Polymer Scientist](https://feeny.ai/job/scientist-ii-senior-melt-polymer-scientist-lila-sciences-cambridge-jc2qn2patfg0) — Cambridge, MA