MATS Autumn 2026

The Autumn 2026 program will run for 10 weeks in Berkeley, CA and London, UK from September 28th to December 4th. Fellows will receive mentorship from world-class researchers and 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. For the first time, we are running Founding & Field-Building and Biosecurity tracks.

Applications are now open. Apply by June 7th.

Program phases

Key dates for the application and admissions timeline

1. Applications

General Application (May 12th to June 7th) 

Applicants fill out a general application to individual tracks which should take 1-2 hours. Applications are due by June 7th EOD AOE.

Additional Evaluations (June 7th to late July)

After an initial evaluation, applicants will apply to individual streams listed below. Additionally, applicants undergo a variety of track specific evaluations including coding tests, writing reviews, work tests, and interviews. Which evaluations you will undergo depend on the tracks, streams and mentors you apply to.

Admissions Decisions (Late July to early August)
Selected applicants are notified of their acceptance and anticipated mentor later in the application cycle.

Autumn 2026 Timeline:

2. Main Program
3. Extension Phase
4. Post-program

Autumn 2026 Streams

In stage one, you apply to one or more tracks (broad research areas): Empirical, Theory, Strategy & Forecasting, Policy & Governance, System Security, Biosecurity, and Founding & Field-Building. In stage two, 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 as a grid here.

Additional streams will be added over the course of May.

This stream is primarily interested in mentoring projects in biosecurity that either (1) create rigorous threat models of AI biological misuse or (2) create benchmarks and tools that allow us to evaluate and mitigate these risks, as well as verifying that companies are taking suitable precautions.

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Mentorship structure
Desired fellow characteristics
Project selection process

This stream focuses on identifying tractable policy and technical interventions to gradual disempowerment, focusing on economic disempowerment and the intelligence curse. Possible project areas include:

  1. Formalizing intelligence curse dynamics into a model that can be tracked and monitored.
  2. More durable policy solutions to mass unemployment than UBI.
  3. Technical interventions to extend the centaur period.
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Mentorship structure
Desired fellow characteristics
Project selection process

This stream focuses on critical challenges in AI safety and alignment, including risks from automating AI research, bottlenecks to recursive self-improvement, and the automation of safety and alignment research. Priority topics also include AGI privacy, measuring long-horizon agentic capabilities, developing new alignment methods, and advancing the science of post-training.

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Mentorship structure
Desired fellow characteristics
Project selection process

Backing projects focused on product development and organization building in the areas of AI safety and alignment, biosecurity, and critical cybersecurity. Looking for fellows who are self starters, default to action, and have a desire to create.

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Mentorship structure
Desired fellow characteristics
Project selection process

In this stream, I’m interested in developing concrete, actionable R&D agendas for post-AGI institutions and AI resilience. For post-AGI institutions, I’m especially interested in what infrastructure would be needed to make super-cooperative AGI or “Coasean bargaining at scale” possible. For AI resilience, I’m interested in follow-on work to airesilience.net that moves from high-level motivation to detailed proposals.

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Mentorship structure
Desired fellow characteristics
Project selection process

Computational/modelling problems in biosecurity.

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Mentorship structure
Desired fellow characteristics
Project selection process

Projects on this stream cluster into a few broad areas from the empirical track: scalable oversight, AI control, monitorability and interpretability, adversarial robustness, and security. 

Most fellows will work closely with one or two mentors on something that fits into the mentors' ongoing research. The above list of mentors above is tentative.

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Desired fellow characteristics

This stream conducts policy and governance research on "loss-of-control" risks from advanced AI, such as recursive self-improvement and misalignment.

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Mentorship structure
Desired fellow characteristics
Project selection process

Community at MATS

MATS Research phase provides scholars with a community of peers.

Scholars work out of a shared office and are supported by the Community Team.

MATS alumni report that the connections with peers that they made during MATS have had the largest impact on them years later. Our full-time Community Team works to facilitate these connections and also provide general well-being support. Weekly lightning talks, scholar-led discussion groups, game nights, and outings to SF are some examples of MATS events.