AI Residency Program, Physical Sciences
BS-level R&D / Research roles on Crosslinked list a median of $130k (383 that show pay). This posting does not list pay.
Run independent AI-for-materials research projects, incl. soft matter and formulation modeling, in a 6-12 month residency.
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Worth knowing
Why it is interesting. Open-ended research on soft matter and formulation intelligence with proprietary datasets and HPC at a well-funded AI science startup
Might not be for you. Fixed 6-12 month residency and computational focus, with no hands-on bench work
Heads-up: Written responses required
Adjacent materials roleAI residency in materials science: soft matter and formulation modeling, composition-process-property models, generative models of colloidal/film morphologies
H-1B filings
Lila Sciences filed 4 H-1B labor applications for scientist and engineer roles from Jan to Dec 2025.
Most common titles: Senior Engineer II, Controls, Senior Engineer II, Automation, Research Associate II. Median filed pay: $145K a year.
From U.S. Department of Labor disclosure data. A filing is a record of past hiring, not a promise about this role, so confirm sponsorship with the employer. Titles and filed pay ·Every employer's filings
- Seniority
- Entry level
- Work
- On-site
- Type
- Full-time
- Degree
- BS
- Industry
- Chemicals
- Role
- R&D / Research
Role details
Your Impact at LILA The Lila Sciences AI Residency is a full-time research program at the intersection of artificial intelligence and materials science. Residents join a cohort of researchers tackling open-ended scientific challenges alongside Lila's scientists and engineers, with the option to focus on fundamental or applied research. Residencies run 6 to 12 months, with extension possible. First residencies begin in spring 2027, with rolling applications and additional intakes in fall 2027. Residents are paired with technical mentors, receive feedback from cross-functional teams, and work with proprietary datasets, high-performance compute, and Lila's research infrastructure.
Publishing is encouraged but not required. What matters most is pushing the frontier of scientific discovery.
Priority research areas for the 2027 cohort span four domains: Soft matter and formulation intelligence: composition-process-property modeling, representation learning for mixtures and formulations, physics-informed and simulation-augmented predictive models, and generative models for 3D soft-material structures at the mesoscale and microscale (colloidal assemblies, phase-separated domains, particle networks, film and bulk morphologies) Physics-based simulation and in silico discovery: agentic frameworks for physics-based and multiphysics or multiscale simulations, and methods that orchestrate and bridge across simulation scales Chemistry-aware AI and molecular design: molecular representations (graphs, protein-ligand structures, MD trajectories), chemistry-reasoning agents, predictive models for synthesis, analysis, and purification, and experimental decision-making under uncertainty and operational constraints Foundational AI for materials science: sequential decision-making under real-world constraints, multimodal learning, reasoning and benchmarking, generative models and representation learning, and scientific machine learning Applications require a resume and a research proposal of up to three pages (unlimited references) outlining the project you would pursue during your residency.
Submit the research proposal as your cover letter. Applications without both documents will not be considered. Optional supporting materials such as recommendation letters, publications, or research artifacts are welcome.
What You'll Be Building Design and execute independent research projects in AI for materials science Pursue work in one or more of the 2027 priority research areas Collaborate with Lila scientists and engineers on open-science initiatives Co-develop novel approaches to scientific discovery with the wider team Use Lila's datasets, compute, and infrastructure to test ambitious hypotheses Share findings internally and externally; publication is welcome, not mandatory What You'll Need to Succeed Degree in materials science, chemistry, computer science, AI/ML, physics, mathematics, or a related field (Bachelor's, Master's, or PhD) Proficiency in Python and deep learning frameworks such as PyTorch Experience working with large-scale datasets or simulations Familiarity with modern AI/ML architectures and training techniques Strong research background shown through publications, thesis work, or open-source projects Bonus Points For Prior ML work in scientific domains such as materials discovery, chemistry, or simulation Experience in one or more of the 2027 priority research areas Open-source contributions or collaborative research experience Clear writing and communication on 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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