The Winter 2027 program will run for 12 weeks, from January 19th to April 10th, in Berkeley, CA and London, UK, with remote options also available. Fellows will receive mentorship from world-class researchers at organizations like Anthropic, Google DeepMind, OpenAI, Redwood Research, and ARC, with the option to apply for a 6–12 month funded extension beyond the main program.
Applications closed on September 6th. Email applications@matsprogram.org with your resume to be considered for a late application.

Key dates for the application and admissions timeline
Applications typically open several months before the program begins. Applicants complete a multi-stage admissions process, beginning with a general application. Depending on the tracks, streams, and mentors they apply to, applicants may also complete additional evaluations such as interviews, work tests, coding assessments, or writing samples before final admissions decisions are made. More information can be found on the apply page.

The main program is a 12 week full-time research fellowship. Fellows work closely with one or more mentors on independent research projects while participating in workshops, talks, office hours, and the broader MATS community. Research directions are developed collaboratively with mentors, with increasing independence throughout the program.
The extension phase typically begins approximately two weeks after the main program concludes. Fellows who demonstrate strong research potential during the main program may apply for a funded 6 to 12 month extension. Extension fellows continue developing independent research with ongoing mentorship and support, typically working from MATS offices or other approved research locations. In recent cohorts, roughly 80% of fellows who applied to the extension phase were accepted.
MATS aims to accelerate researchers who will:
MATS alumni have gone on to publish safety research, join alignment organizations–including Anthropic and MIRI–and found an alignment research lab. You can read more about MATS alumni here.
In Stage 1, applicants apply to one or more tracks (broad research areas): Empirical, Theory, Strategy & Forecasting, Policy & Governance, System Security, Biosecurity, and Founding & Field-Building. In Stage 2, advancing applicants choose specific streams within those tracks, each led by one or more mentors with their own research agenda. You can view this list below or as a grid here.
Agent Foundations research focused on clarifying conditions under which humans can justifiably trust artificial intelligence systems. When should one boundedly rational learning-theoretic process come to trust another?
We can discuss this more and decide on a different structure, but by default, 1 hour 1-on-1 meetings with each scholar once a week, plus a 2 hour group meeting which may also include outside collaborators.
Quality of fit is roughly proportional to philosophical skill times mathematical skill. Someone with excellent philosophical depth and almost no mathematics could be an OK fit, but would probably struggle to produce or evaluate proofs. Someone with excellent mathematical depth but no philosophy could be an OK fit, but might struggle to understand what assumptions and theorems are useful/interesting.
There will be some flexibility about what specific projects scholars will pursue. Abram will discuss the current state of his research with scholars and what topics scholars are interested in, aiming to settle on a topic by or before week 2.
In my stream, I focus on empirically measuring how frontier AI changes human capabilities in biology and the implications of it for biological risk. I’m particularly interested in real-world evaluations, understanding what drives AI-enabled uplift, and developing simulations or other proxies that can be validated against physical experiments and used to rapidly assess new models.
TBD. Please check back later for details. Broadly speaking I'm open to a wide range of projects across AI policy and technical AI governance, and I'm open to pitches. Right now I'm sorting out some career plans that will affect the kinds of projects that I'd support.
Strong understanding of the AI x-risk worldview, including detailed and well-informed views on AI timelines, the most important threats, the key technical and policy solutions, etc.
Strong writing ability, autonomy, and a track record of having led large impressive projects
TBD
We are interested in mentoring projects in AI forecasting, governance, and strategy. We want to improve the epistemic environment around thinking about AI risk by putting out concrete scenarios, exploring different dynamics and worlds that might happen, trying to forecast how things will go, and sometimes talking about how to deal with the risks. We hope that having better resources for thinking about the future will lead to better outcomes.
We will have meetings each week to check in and discuss next steps. We will be consistently available on Slack in between meetings to discuss your research, project TODOs, etc.
The most important characteristics include:
We will talk through project ideas with scholar
This stream works on the AI Village, where more than twenty frontier agents act in the real world over thousands of hours. Projects either mine the existing record of agent reasoning, messages and actions for new insight, or run new experiments in the Village to test hypotheses about multi-agent dynamics and real-world evaluation.
This stream will focus on field-building and research amplification, including headhunting and talent projects, ecosystem incentives such as large impact bounties, and operational work to scale an alignment research team.
Strong motivation to reduce loss-of-control risks from misaligned superintelligence.
One of the following:
1. Impressive experience outside AI safety, for example: successfully scaling a startup as an early hire, 5 years at a top consultancy with above-average progression, or an unusually strong background from a leading tech company.
2. A strong AI safety operational track record, like leading a research fellowship, or talent program.
This stream focuses on secret loyalties, where an LLM covertly tries to advance a principal's interests. Secret loyalties have been established as a pressing threat [1], and model organisms of narrow secret loyalties have been constructed and audited [2]. This stream aims to advance the empirical foundations of our understanding of secret loyalties. The goal being that humanity is well-equipped to deal with secret loyalty installation attempts as and when catastrophic secret loyalties become possible in the future.
We think being well-equipped looks like having sufficient security measures in place in frontier AI companies, understanding the dynamics and behaviours of secretly loyal AI systems, having effective auditing and verification protocols for secret loyalties and attempts to install them, and these protocols actually being followed by relevant stakeholders.
The Alignment Research Center is a small non-profit research group based in Berkeley, California, that is working on a systematic and theoretically grounded approach to mechanistically explaining neural network behavior. We are interested in fellows with a strong math background and mathematical maturity. If you'd be excited to work on the research direction described in this blog post – then we'd encourage you to apply!
Scholars will work out of ARC's offices in Berkeley. Each scholar will meet with their mentor at least once a week for an hour, though 2-3 hours per week is not uncommon. Besides time with their official mentor, scholars will likely spend time working in collaboration with other researchers; a typical scholar will likely spend about 25% of their time actively collaborating or learning about others' research.
Each scholar will be paired with the mentor that best suits their skills and interests. The mentor will discuss potential projects with the scholar, and they will decide what project makes the most sense, based on ARC's research goals and the scholar's preferences.
Most scholars will work on multiple projects over the course of their time at ARC, and some scholars will work with multiple mentors.
The MATS Program is supported by a diverse and highly respected group of mentors — top-tier researchers, engineers, and thinkers working across AI alignment, governance, interpretability, and security.
The timeline for the MATS Winter 2027 program is:
Based on stream rankings of applicants and applicant rankings of streams, a final matching process uses both sides' rankings to send out a single offer.
How long does the application process take?
Stage 1 applications open on August 18th and close on September 6th, end of day anywhere on Earth. Offers go out in early to mid-November, and the program starts on January 19th.
A track is a broad research area within MATS. Empirical, Theory, Strategy & Forecasting, Policy & Governance, Systems Security, Founder & Field-Building, and Biosecurity are our current tracks. Each track contains multiple streams. In Stage 1, you apply to tracks.
Streams are organized around a research agenda, led by one or more mentors who guide fellows through related projects. In Stage 2, applicants apply to streams within tracks based on research that interests them.
You may apply to as many tracks as you wish at Stage 1. At Stage 2, depending on which tracks you progress in, you may then apply to as many streams as you wish within those tracks; there is no cap. The process is comparable to applying to PhD supervisors.
We want to be flexible for applicants who have urgent prior commitments. Based on individual circumstances, we may be willing to alter the time commitment of the program and allow fellows to leave early or arrive late. Please inform us of your availability in the application process.
Applicants who will be 18 years or older before the program start date are eligible to apply. Both US and non-US citizens are eligible to apply. All backgrounds and levels of experience are welcome and prior AI safety experience is not required.
Yes. The 12-week program requires fellows to commit 40 hours per week to their MATS research. For exceptionally strong candidates with significant concurrent responsibilities, the time commitment can be reduced to 20 hours per week on a case-by-case review. However, the program maintains an expectation of sustained, high-level engagement, including regular participation in core activities and most organized events. Candidates that require a J1 visa to come to the US are unable to participate part time; they can only work part time if they participate remotely or from the UK.
Yes, upon submitting you will receive a link that lets you edit your response. Please note that you will not be able to edit your response once the application period ends.
LLMs may not be used to write any part of your application unless specific work tests or forms explicitly permit it. MATS monitors for LLM use, and applicants found to have used LLMs may be disqualified.
Depending on the evaluations of the tracks and streams you apply to in Stages 1 and 2, we will contact your references. We will send them a form with our own set of questions, so they will not have to prepare a reference letter.
MATS provides a stipend of $1600 per week for participation in the main program ($19,200 for the full 12-week program). Scholars who are participating and performing research for less than 40 hours/week and/or for less than 12 weeks will receive stipends proportional to their level of participation.
Separately from this stipend, MATS will provide scholars with travel to and from Berkeley or London, housing, office space, and lunch and dinner on weekdays.
MATS participants may have to pay taxes on their grants based on the rules of the countries in which they are a resident for tax purposes. The grants should be regarded as private grants from a non-profit entity provided to individuals for the purpose of independent research and participation in a US-based educational seminar program.
Although MATS sometimes supports UC Berkeley-based mentors, MATS is an independent program and is not formally part of UC Berkeley. As such, MATS will not be providing student cards to our scholars.
The main program, or Research Phase, takes place in person in Berkeley, CA and London, UK. Historically, most fellows participate from Berkeley. London is typically chosen by fellows who want to co-locate with their mentor or who have a preference to work from the UK instead of US.Will this program be remote or in-person?
The main program, or the Research Phase takes place in Berkeley, CA and London, UK, with the majority of fellows participating from Berkeley. We strongly encourage in-person participation when possible, as a core part of the program experience comes from day-to-day interactions with your cohort and others in the broader AI safety ecosystem.
Decisions about remote participation are made on a case-by-case basis and depend primarily on mentor preferences, many of whom are open to the possibility, especially if you have family or other obligations that make in-person participation difficult. We strongly encourage in-person participation when possible, as a core part of the program experience comes from day-to-day interactions with your cohort and others in the broader AI safety ecosystem.
If you have difficulties in securing a visa to participate from Berkeley, we are likely to be able to support participation from our London office.The 6–12 month extension gives fellows the option to participate from Berkeley, London, or remotely.
MATS is a scientific and educational seminar and independent research program, and provides J1 visas for non-American participants. Participants can also opt to participate from our London office; however, please note that visa support is not available for that option.
During the main program, fellows should expect to meet with their mentor for at least one hour per week, with more frequent communication via Slack. The extent of mentor support will vary depending on the project and the mentor.
Fellows will also receive support from MATS’ Research Management team, who work with mentors by tracking scholar research progress, unblocking scholar research, and assisting with grant applications and deadlines.
Fellows develop as researchers by working with an experienced research mentor, interacting with other fellows, and receiving support from our Research Management team. Research managers meet weekly with most fellows and mentors and help with research strategy, research unblocking, and project coordination.
Other forms of training include workshops on different parts of the research process and seminars on a variety of AI technical safety and governance research.
Throughout the program, each fellow will work on an independent research project with input and guidance from your mentor(s). Depending on which stream you participate in, you may collaborate with other fellows in your stream.
Traditionally, fellows submit a Research Plan midway through the program and present their research at the Fellow Symposium at the end of the program.
We welcome feedback. For feedback for the whole team (visible by all MATS staff), please use this form. For feedback that will only be visible to the Co-Executive Directors, Ryan and Christian, please submit here.
You can contact the MATS Board of Directors using this linked form (responses are only viewable by the Board). Please only use this if you feel your question or concern requires board-level attention.