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AI Residency Program, Material Science (2026 Cohort)
Lila Sciences · Cambridge, MA USA · Active · Greenhouse
Job facts
| Field | Value |
|---|---|
| Company | Lila Sciences |
| Title | AI Residency Program, Material Science (2026 Cohort) |
| Normalized title | - |
| Department / team | Physical Sciences AI |
| Location | Cambridge, MA, United States |
| Work model | - |
| Employment type | - |
| Salary | - |
| Status | active |
| ATS provider | Greenhouse |
| Posted / first seen | 2025-10-06 / 2026-05-29 |
| Changed / last seen | 2026-05-29 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Lila Sciences. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Greenhouse. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in Cambridge. | Open |
| Department jobs | Active postings in Physical Sciences AI. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Lila Sciences |
| Source | a1e67975-fd33-4f8d-940f-2dbc2480c450 |
| ATS provider | Greenhouse |
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.
Full job record
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| Board ID | a1e67975-fd33-4f8d-940f-2dbc2480c450 |
| Provider | greenhouse |
| Provider Job Key | 4031379009 |
| Title | AI Residency Program, Material Science (2026 Cohort) |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Cambridge, MA USA |
| Department | Physical Sciences AI |
| Team | — |
| Employment Type | — |
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| Remote Policy | — |
| Country | United States |
| Region | MA |
| City | Cambridge |
| Salary Raw | — |
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| Source URL | https://job-boards.greenhouse.io/lilasciences/jobs/4031379009 |
| Apply URL | https://job-boards.greenhouse.io/lilasciences/jobs/4031379009 |
| First Seen At | 2026-05-29 23:01:25Z |
| Last Seen At | 2026-06-06 07:34:08Z |
| Last Checked At | 2026-06-06 07:34:08Z |
| Last Changed At | 2026-05-29 23:01:25Z |
| Inactive At | — |
| Source Posted At | 2025-10-06 17:26:40Z |
| Source Updated At | 2026-05-15 15:12:57Z |
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