Research
Residency
A research home for people who want to understand intelligence — not just build with it. We study how intelligence manifests in biological systems, then use that inspiration to build artificial systems that go beyond where current AI falls short.
Three programs. One shared obsession.
We define intelligent systems as those that achieve their goals successfully, even in situations they haven't encountered before.
Most AI systems today are brittle outside the training distribution. They can be extraordinarily capable within a narrow window — and completely lost the moment conditions shift. We think this is the central unsolved problem in AI: not more scale, but genuine adaptability.
Our belief is that the path forward runs through biology. Evolution has produced systems — brains, bodies, ecosystems — that adapt, generalize, and create under conditions no designer specified. Understanding those systems deeply gives us a blueprint. Not to copy them, but to be inspired by the principles they embody.
The Glitter Research Residency exists for people who share this conviction and want to spend serious time working on it.
Find Your Program
We've designed four distinct entry points into our research community — each calibrated to a different stage of your career and style of inquiry.
Research Fellowship
A full-time, year-long research position based out of our Nagpur lab. Designed for pre-doctoral researchers and post-docs who want sustained, uninterrupted time to pursue foundational questions at the intersection of artificial and biological intelligence.
Research Internship
A structured research internship for undergraduate and graduate students who are serious about AI research. You'll work alongside our research team on a real problem, contribute meaningfully to ongoing projects, and leave with a publication-track result or research artifact.
Residency
A six-week, on-site, curiosity-led exploration into AI and related topics. The Residency is for people who don't fit the standard academic mold but have a deep, genuine drive to understand how intelligence works. No formal research background required. Intellectual seriousness is.
Forward Deployed Engineering Fellow
Embed directly with our customer teams and help deploy AI systems that solve real problems on day one. This is not an internship — it's a high-intensity, hands-on engineering fellowship where you bridge the gap between AI product and production. You'll travel on-site, understand customer workflows deeply, and build bespoke AI integrations that ship within your fellowship window.
Program Comparison
| Program | Who it's for | Duration | Format | Stipend |
|---|---|---|---|---|
| Fellowship | Pre-doc, post-doc researchers | 1 year | Full-time, on-site | Competitive + housing |
| Internship | Undergraduate & graduate students | 3–6 months | Full-time, on-site | Stipend provided |
| Residency | Curious minds, non-traditional paths | 6 weeks | Full-time, on-site | Travel grant + housing |
| Fwd. Deployed | Grad & early-career engineers | 12 weeks | Full-time, on-site | Paid stipend |
What We Study
Our research organizes around three interconnected directions — all aimed at the same underlying question: what does it actually take for a system to be intelligent?
AI that Adapts to a Domain
Intelligence isn't static. Biological systems continuously update their models of the world from experience, generalize beyond what they've seen, and operate gracefully under uncertainty. We want to understand what mechanisms make this possible — and replicate them in artificial systems that learn continuously, adapt efficiently, and act with appropriate confidence.
Creativity in Artificial Systems
Current AI systems recombine — but rarely create. True creativity involves generating ideas that are novel, surprising, and valuable: forming new abstractions, building world models that extrapolate beyond training data, and producing outputs that expand the boundaries of a domain. We study the computational and representational foundations of creative cognition, in both humans and machines.
Biological Foundations of Intelligence
The most sophisticated intelligent systems on Earth were not designed — they evolved. Understanding how biological systems develop intelligence, from neural wiring to developmental cognition to the emergence of language, gives us a window into principles that no current AI architecture has fully captured. We study these systems directly, not just as metaphors.
We deliberately keep our research directions broad at the boundary but tight in execution. Residents and fellows are expected to go deep — to pick a specific question within one of these directions and pursue it with intensity. Shallow breadth doesn't produce insight. We believe the most interesting results come from people willing to sit with a hard problem long enough for it to break open.
Life at the Lab
What being here actually looks like — day to day, week to week.
Structured but Unscheduled
The lab has a rhythm — weekly seminars, reading groups, and project check-ins — but most of your time is unstructured deep work. We don't fill calendars. We protect thinking time.
Collaborative, Not Competitive
Ideas travel freely here. People debug each other's thinking, share half-formed intuitions, and argue in good faith. The lab culture is one where being wrong is fine — being uncurious isn't.
Rooted in Nagpur
Our Nagpur lab is a physical place where things happen in real space and time. The city has a dense, growing AI research community — we're embedded in it and active within it.
Connected to the Global Community
We host visiting researchers, co-author with labs around the world, and present at major venues. Being here puts you in the conversation — not on the periphery of it.
Publication as a Byproduct
We don't chase publications — we chase understanding. But deep, original work tends to produce results worth sharing. Fellows and interns regularly co-author papers at top venues.
Long Time Horizons
We're working on problems that don't have solutions yet. Residents aren't expected to solve them — they're expected to make the problem clearer. Progress here looks like better questions, not just better benchmarks.
Who We're Looking For
There is no single profile. But there are patterns.
The best applicants come with something they're already itching to explore. Tell us what you're thinking about — even if it's half-formed.
Some of our best insights have come from neuroscience papers read by ML researchers, or philosophy of mind read by engineers. Breadth of reading is a signal we look for.
Foundational research means working on problems where there's no clear metric of success. If you need a leaderboard to feel productive, this isn't the right fit.
Whether code, writing, experiments, or models — we value people who turn ideas into artifacts. The artifact is how you learn whether the idea was right.
We've had residents from computer science, cognitive science, linguistics, mathematics, and philosophy. Formal credentials matter less than how you think and what you've taught yourself.
Ready to Apply?
Send us an email at research@glitterlabs.com with the subject line matching your program of interest.
Include a short note about what you want to explore, why now, and why here. No CV template required — tell us about your thinking, not your credentials.
We review applications on a rolling basis. Cohorts typically start in January, May, and September. If your timeline is different, mention it — we're flexible for the right candidate.