Research Scientist, Porous Materials

Your Impact at Lila

As a Scientist/Senior Scientist on our Physical Sciences team, you will design advanced synthesis platforms for the synthesis and characterization of zeolitic materials. Your work will be enabling high-throughput experimentation integrated with real-time analytics. Collaborating across chemistry, material science, machine learning, and data science teams, you’ll help establish next-generation tools for advanced porous material development platforms.

What You'll Be Building

• Design & Commission: Design and validate systems for synthesis of zeolitic and other types of porous materials with the help of our automation engineering team.
• Integrate & Scale: Interface near real-time high throughput characterization tools with platforms to enable feedback-driven synthesis and formulation.
• Workflow Optimization: Integrate the synthesis platforms with robotics and software pipelines for automated high-throughput experimentation and data-rich workflows.
• Closed-Loop Execution: Collaborate with AI teams to run iterative experiments in real time, enabling fast optimization and discovery cycles.
• Collaboration & Documentation: Work with chemists, material scientists, engineers, and data scientists to document systems, share insights, and refine best practices in autonomous porous material chemistry.

What You’ll Need to Succeed

• Ph.D. or M.S. in Chemistry, Chemical Engineering, Material Science or a related field.
• ≥ 5 years of hands-on experience in zeolitic material synthesis.
• Deep expertise in porous material characterization
• Experience in integrating analytical instruments into automated or modular experimentation platforms.
• Experience in high throughput synthesis and characterization techniques.
• Excellent troubleshooting, communication, and interdisciplinary collaboration skills; ability to both innovate and communicate cross-functionally across materials science domains.
• Experience in powder x-ray diffraction technique and data analysis (indexing, and refinement)

Bonus Points For

• Proficiency in Python or other scripting languages for data analysis.
• Experience with self-driving lab platforms or closed-loop optimization systems.
• Knowledge of design-of-experiment (DoE) methods and Bayesian optimization.
• Experience contributing to scientific software tools or open-source automation frameworks.

About Lila

Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at www.lila.ai

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, we encourage you to apply.

Compensation

We expect the base salary for this role to fall between $108,000–$150,000 USD per year, along with bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact.

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 thereto.