Your Impact at LILA

The Lila Sciences AI Residency is a full-time research program at the intersection of artificial intelligence and materials science. Residents join a cohort of researchers tackling open-ended scientific challenges alongside Lila's scientists and engineers, with the option to focus on fundamental or applied research.

Residencies run 6 to 12 months, with extension possible. First residencies begin in spring 2027, with rolling applications and additional intakes in fall 2027. Residents are paired with technical mentors, receive feedback from cross-functional teams, and work with proprietary datasets, high-performance compute, and Lila's research infrastructure. Publishing is encouraged but not required. What matters most is pushing the frontier of scientific discovery.

Priority research areas for the 2027 cohort span four domains:

• Soft matter and formulation intelligence: composition-process-property modeling, representation learning for mixtures and formulations, physics-informed and simulation-augmented predictive models, and generative models for 3D soft-material structures at the mesoscale and microscale (colloidal assemblies, phase-separated domains, particle networks, film and bulk morphologies)
• Physics-based simulation and in silico discovery: agentic frameworks for physics-based and multiphysics or multiscale simulations, and methods that orchestrate and bridge across simulation scales
• Chemistry-aware AI and molecular design: molecular representations (graphs, protein-ligand structures, MD trajectories), chemistry-reasoning agents, predictive models for synthesis, analysis, and purification, and experimental decision-making under uncertainty and operational constraints
• Foundational AI for materials science: sequential decision-making under real-world constraints, multimodal learning, reasoning and benchmarking, generative models and representation learning, and scientific machine learning

Applications require a resume and a research proposal of up to three pages (unlimited references) outlining the project you would pursue during your residency. Submit the research proposal as your cover letter. Applications without both documents will not be considered. Optional supporting materials such as recommendation letters, publications, or research artifacts are welcome.

What You'll Be Building

• Design and execute independent research projects in AI for materials science
• Pursue work in one or more of the 2027 priority research areas
• Collaborate with Lila scientists and engineers on open-science initiatives
• Co-develop novel approaches to scientific discovery with the wider team
• Use Lila's datasets, compute, and infrastructure to test ambitious hypotheses
• Share findings internally and externally; publication is welcome, not mandatory

What You'll Need to Succeed

• Degree in materials science, chemistry, computer science, AI/ML, physics, mathematics, or a related field (Bachelor's, Master's, or PhD)
• Proficiency in Python and deep learning frameworks such as PyTorch
• Experience working with large-scale datasets or simulations
• Familiarity with modern AI/ML architectures and training techniques
• Strong research background shown through publications, thesis work, or open-source projects

Bonus Points For

• Prior ML work in scientific domains such as materials discovery, chemistry, or simulation
• Experience in one or more of the 2027 priority research areas
• Open-source contributions or collaborative research experience
• Clear writing and communication on complex scientific ideas