Job Board
LogoLogo

Get Jobs Tailored to Your Resume

Filtr uses AI to scan 1000+ jobs and finds postings that perfectly matches your resume

Pioneering Intelligence Logo

Research Scientist, Porous Materials

Pioneering Intelligence

Salary not specified
Sep 12, 2025
Cambridge, MA, US
Apply Now

Lila Sciences is solving humankind's greatest challenges by applying AI to every aspect of the scientific method, enabling solutions in human health, climate, and sustainability at an unprecedented pace and scale.

Requirements

  • ≥ 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.
  • Experience in powder x-ray diffraction technique and data analysis (indexing, and refinement).
  • Proficiency in Python or other scripting languages for data analysis.
  • Experience with self-driving lab platforms or closed-loop optimization systems.

Responsibilities

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

Other

  • Ph.D. or M.S. in Chemistry, Chemical Engineering, Material Science or a related field.
  • Excellent troubleshooting, communication, and interdisciplinary collaboration skills; ability to both innovate and communicate cross-functionally across materials science domains.
  • Knowledge of design-of-experiment (DoE) methods and Bayesian optimization.
  • Experience contributing to scientific software tools or open-source automation frameworks.
  • Ability to work in a collaborative and inclusive environment where all voices are heard.