The Stanford Existential Risks Initiative (SERI) recently opened applications for the Winter 2022 Cohort of the ML Alignment Theory Scholars (MATS) Program, which aims to help aspiring alignment researchers enter the field by facilitating research seminars, workshops, an academic community, and an independent research project with an alignment research mentor. Applications close on Oct 24 and include a written response to (potentially hard) mentor-specific selection questions, viewable on our website.

Our current mentors include Alex Turner, Andrew Critch, Beth Barnes, Dan Hendrycks, Evan Hubinger, Jesse Clifton, John Wentworth, Nate Soares, Neel Nanda, Owain Evans, Quintin Pope, Rebecca Gorman, Richard Ngo, Stuart Armstrong, Vanessa Kosoy, Victoria Krakovna, and Vivek Hebbar.

Program details

MATS is a scientific and educational seminar and independent research program, intended to serve as an introduction to the field of AI alignment and allow networking with alignment researchers and institutions. The MATS Program Winter 2022 Cohort consists of:

A 6-week online training program (averaging 10-20 h/week from Nov 7 to Dec 14);
A 2-month in-person educational seminar and independent research program in Berkeley, California for select scholars (40 h/week from Jan 3 to Feb 24); and
Possible ongoing 2-month extensions for select scholars, potentially in Berkeley, California or London, UK.

During the research phase of the program, mentors will meet with scholars for around 1-2 h/week to share their research agenda and supervise the scholars’ research projects. Scholars' research directions will initially be chosen by the mentors, but by default, scholars are expected to develop their independent research direction as the program continues. Educational seminars and workshops will be held 2-3 times per week, similar to our Summer Seminar Program.

The MATS program is a joint initiative by the Stanford Existential Risks Initiative and the Berkeley Existential Risk Initiative, with support from Lightcone Infrastructure and Conjecture. We receive financial support from the Long-Term Future Fund.

Who is this program for?

Our ideal applicant has:

an understanding of the AI alignment research landscape equivalent to having completed the AGI Safety Fundamentals course;
previous experience with technical research (e.g. ML, CS, maths, physics, neuroscience, etc.), ide

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