neuromorphic computing program
the von neumann architecture that powers modern computing is approaching physical and efficiency limits. neuromorphic computing—inspired by biological neural systems—offers an alternative computational paradigm that may address several critical challenges in current computing systems:
- energy efficiency: biological neural systems perform complex computations with minimal energy requirements
- real-time processing: event-driven computation enables responsive systems without clock-driven overhead
- adaptability: robust performance in uncertain and noisy environments
the neuromorphics program is a six-month research program through the residency for talented researchers and engineers focused on next-gen computation. we aim to advance spiking neural networks (snns) and neuromorphic hardware through collaborative research, rapid prototyping, and first-principles thinking.
participants receive mentorship from academic and industry experts, access to neuromorphic hardware, and participate in lectures, research workshops, and hands-on sessions. this will be highly rigorous and collaborative.
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program structure
- research freedom: drive ambitious projects with substantial autonomy
- collaborative setting: work alongside peers in a focused, high-trust environment
- expert guidance: connect with leaders in neuromorphics, robotics, audio systems, and ai
- learning opportunities: engage in weekly lectures on neuromorphics, theory of computation reading groups, coding sessions, and research workshops
- technology access: use cutting-edge neuromorphic chips and embedded systems in real projects
- presentations and feedback: share your work regularly and receive substantive critique
- time commitment: full-time preferred; part-time (20+ hours/week) considered for significant contributors
candidate profile
we welcome researchers and engineers from diverse technical backgrounds including cs, neuroscience, physics, ee, mathematics, and ml. specific neuromorphic computing experience is not required.
ideal candidates demonstrate:
- substantial technical expertise in their field
- self-direction in tackling complex research challenges
- interest in fundamental research questions
- fascination with unconventional and biologically-inspired computing approaches
faq
do i need a background in neuromorphic computing?
nope. if you’re deeply technical and curious, that’s enough. we’re looking for people who are eager to learn, question assumptions, and think from first principles.
where is the program based?
the in-person cohort is based in new york city. if you already live in the city and aren’t open to moving, we will still consider you.
how much time do i need to commit?
ideally full-time. but if you can commit at least 20 hours a week and show up consistently, we’re open to part-time participants.
is this a class, an internship, or a job?
none of the above. it’s closer to an independent research fellowship—self-directed but collaborative.
will i get access to neuromorphic hardware?
yes. depending on your project, we’ll help you access chips, tools, and relevant datasets. this includes potential collaboration with startup and academic labs.
what happens after the six months?
if the work is promising, we’ll help you continue—whether that’s through grants, startup funding, or a more permanent lab or hub.
is this funded?
we’re currently self-funded, like a hacker house. we’re working to secure funding to support participants. the cost is rent in our apartment.
application information
applications reviewed on a rolling basis. program begins july 2025. for details or to apply, contact madhu2423@gmail.com.
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