Job Opportunities API

AI Resident – 2026 Cohort 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