AI Residency Program, Material Science (2026 Cohort)
Lila Sciences · On-site
MeritLog read this listing from Lila Sciences's Greenhouse job board and last checked it on September 12, 2026.
Source: the employer's Greenhouse job board. Open the original listing for current details.
Job details
- Work model
- On-site
- Salary
- Not listed by source
- Location
- Cambridge, MA USA
Hiring context
How this role compares at Lila Sciences
Lila Sciences has 115 live roles in MeritLog’s catalog across 9 job families, and 52 of them are in data & analytics. 0 of those listings publish a pay range, a disclosure rate of 0%.
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What the role asks for
What they're asking for
- Prior work on ML applications in scientific domains (e.g., materials discovery, chemistry, simulations)SkillPreferred
- Familiarity with Bayesian optimization, active learning, or generative modelsSkillPreferred
- Experience in reinforcement learning or agent-based approaches to scientific reasoningSkillPreferred
- Open-source contributions or collaborative research experienceSkillPreferred
- Strong communication and writing skills, especially for conveying complex scientific ideasSkillPreferred
Parsed by MeritLog from the employer’s own posting. The full description follows below.
Job description
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 autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.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 an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. 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. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy. 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.
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