AI Residency Program, Material Science; Cohort

AI Residency Program, Material Science (2026 Cohort)

Cambridge, MA USA

The AI Residency Program is a full-time research opportunity designed to bridge the gap between academic research and industry applications in AI for materials science. Residents will work closely with Lila scientists and engineers on high-impact, open-science projects, with the option to focus on either fundamental or applied research.

• Duration: 6–12 months (extension possible)
• Start Dates:
  First hires beginning January 2026, with rolling applications and additional intakes in Summer and Fall 2026
• Cohort Size:
  Small group of selected residents
• Mentorship:
  Pairing with technical mentors, feedback from cross-functional teams
• Resources:
  Access to proprietary datasets, high-performance compute, and Lila's research infrastructure

Research areas include ML-accelerated simulations, Bayesian methods, representation learning, generative models, agentic science, and ML-driven automation.

Application Requirement:
Please submit your resume alongside a research proposal (up to 3 pages, unlimited references) outlining the project you would plan to pursue during your residency at Lila Sciences.

Please submit your research proposal as your cover letter. Applications without both documents will not be considered. Optional supporting materials (e.g., recommendation letters, publications, research artifacts) may also be included.

Your Impact at Lila

The Lila Sciences AI Residency is a full-time research program at the intersection of artificial intelligence and materials science. As a resident, you'll join a cohort of researchers tackling open-ended scientific challenges alongside Lila's world-class team of scientists and engineers. With access to proprietary datasets, high-performance compute infrastructure, and experienced mentors, you'll pursue ambitious research projects with both academic and real-world impact.

Publishing is encouraged but not required — what matters most is pushing the frontier of scientific discovery.

What You'll Be Building

• Design and execute independent research projects in AI for materials science
• Collaborate with Lila scientists and engineers on cutting-edge, open-science initiatives
• Explore domains such as ML-accelerated simulations, Bayesian methods, representation learning, generative AI, agentic science, and ML-driven automation
• Contribute to collaborative team research and co-develop novel approaches to scientific discovery
• Share findings internally and externally; publications are welcome but not mandatory

What You'll Need to Succeed

• Degree in Materials Science, Chemistry, Computer Science, AI/ML, Physics, Mathematics, or related field (Bachelor's, Master's, or PhD)
• Proficiency in Python and deep learning frameworks (e.g., PyTorch)
• Experience working with large-scale datasets or simulations
• Familiarity with modern AI/ML architectures and training techniques
• Strong research background, demonstrated through publications, thesis work, or open-source projects

Bonus Points For

• Prior work on ML applications in scientific domains (e.g., materials discovery, chemistry, simulations)
• Familiarity with Bayesian optimization, active learning, or generative models
• Experience in reinforcement learning or agent-based approaches to scientific reasoning
• Open-source contributions or collaborative research experience
• Strong communication and writing skills, especially for conveying complex scientific ideas

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 a.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…