Lila Sciences, Inc.
AI Residency Program, Material Science (2026 Cohort)
Lila Sciences, Inc., Cambridge, Massachusetts, us, 02140
AI Residency Program, Material Science (2026 Cohort)
Cambridge, MA 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:
612 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 Lilas 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. Lila Sciences is the worlds first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at www.lila.ai. If this sounds like an environment youd love to work in, even if you only have some of the experience listed below, we encourage you to apply. What Youll Need to Succeed
Degree in Materials Science, Chemistry, Computer Science, AI/ML, Physics, Mathematics, or related field (Bachelors, Masters, 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 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 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. 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 Sciences 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. #J-18808-Ljbffr
Cambridge, MA 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:
612 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 Lilas 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. Lila Sciences is the worlds first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at www.lila.ai. If this sounds like an environment youd love to work in, even if you only have some of the experience listed below, we encourage you to apply. What Youll Need to Succeed
Degree in Materials Science, Chemistry, Computer Science, AI/ML, Physics, Mathematics, or related field (Bachelors, Masters, 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 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 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. 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 Sciences 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. #J-18808-Ljbffr