Doing research in MLC is not too different from doing research elsewhere. You need a few key components to get started: an idea (e.g. *"I want to stabilize GAN training"*), any number of collaborators (can be zero), a regimen (e.g. *"working on it X hours a week"*) and a target (e.g. *"publishing it at conference Y"*). And all of these should be established upfront and revised constantly over time.

But one key difference of doing research in MLC — or any non-traditional, non-institutionalized setting — is that none of the above *come as a given*. While in a grad school lab, or an employment based research lab, you may be handed an idea, automatically assigned to a team, naturally following a regimen imposed by exams, qualifiers, perf reviews and/or just peer pressure, and have a target to graduate, or be promoted, here, you will have to act proactively on your own to gather all those ingredients onto your plate. 

Why the difference? Well, in the former, that is, institution-based learning, barriers are set up *so that* opportunities and participation are reserved to only a selected few. You have to pass lots of screenings, interviews, admissions to gain access to resources and opportunities. In the open science regime that MLC operates in, there's no cost to entry, but you have to prove your worth through the *actual work of doing research*: 

* find your own idea: e.g. browsing the pool of [RFPs](, attending [research jams]( and [reading groups](, participating in open science events and initiatives, and actively thinking;
* seek out for your own collaborators: e.g. posting in `#seek-collaborator` channel on the MLC Discord, reach out to people that have published similar work;
* set up your own regimen with a lot of self discipline, e.g. commit to presenting at every [research jam]( to push yourself to make decent progress. 
* set your own target and follow through.

For each component there are existing resources in MLC, but you will have to be the one that *actively use them*. It may sound harder, and indeed it is harder to have to self-motivate, self-examine, and take responsibility of your path (instead of relying on an assigned advisor or manager) from the start. But we believe you'll come out a better trained researcher this way.

This article was last modified: Oct. 27, 2021, 5:33 a.m. UTC

Powered by django-wiki, an open source application under the GPLv3 license.