AI Residency Program, Material Science (2026 Cohort)

3 мес. назад

USATrainee

machine learningbayesian methodsrepresentation learninggenerative models

A full-time AI residency research program focused on bridging academic research and industry applications in AI for materials science.

Будет плюсом

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

Другое

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.
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.
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
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
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
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.
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 .
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.