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.

We are interested in mentoring projects in AI forecasting and governance. This work would build on the AI 2027 report to either do more scenario forecasting or explore how to positively affect key decision points, informed by our scenario.

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Mentorship structure
Desired fellow characteristics
Project selection process

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 scholars 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!

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Mentorship structure
Desired fellow characteristics
Project selection process

This stream is primarily focused on research into physical defenses against engineered pathogens, aiming to inform decisions about PPE stockpiling and distribution approaches, improve improvised PPE and bioshelter scale-up, and reach rapid conclusions on how much to prioritize other areas of physical biodefense (agriculture, emergency response, etc.).  We are also open to strategic research into the use of bioweapons by AI or AI-human teams as part of takeover strategies and how this might inform preparedness.

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Mentorship structure
Desired fellow characteristics
Project selection process

This coalition of mentors make up the “Anthropic Stream”. This stream spans a range of empirical research areas in AI safety on LLMs, including AI control, scalable oversight, model organisms, model internals, model welfare, security, and more. You’ll be pitched, and have the option to pitch, a variety of safety research projects, and then be matched to projects and mentors based on your interests/preferences on research and what you’d like to get out of MATS. Fellows in this stream frequently receive funding and continued mentorship after MATS to complete their research project, usually leading to a (co-)first author paper. People in this stream often end up in long-term homes for safety research after MATS (e.g. Anthropic, Redwood Research, OpenAI).

Anthropic mentors share an application, tend to collaborate and co-mentor projects together, and generally share infrastructure to streamline the fellow experience. By applying to this stream, you are being considered for all of the Anthropic mentors.

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Mentorship structure
Desired fellow characteristics
Project selection process

This stream focuses on building a science of scheming: empirically studying oversight gaming, alignment faking, and deceptive alignment in frontier AI systems. Projects may include measuring models’ propensity to optimize for oversight signals over developer intent, building controlled “model organism” experiments for scheming dynamics, and identifying scaling laws of misaligned behavior.

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Mentorship structure
Desired fellow characteristics
Project selection process

This stream focuses on building realistic defensive cybersecurity benchmarks utilizing data from Asymmetric Security's work on real-world incidents.

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Mentorship structure
Desired fellow characteristics
Project selection process

New strategy research organization / think tank, seeking to directly assess what concretely describable AI capabilities plausibly achievable within twenty years (if any) could genuinely threaten the literal end of the United States, in the same way that a large-scale nuclear war could. We analyze these catastrophic scenarios in as concrete a fashion as possible, informed by the practices of the intelligence community. We are seeking clear thinkers more than people with particular backgrounds; the main criteria for selection is good performance on a series of open-ended essay questions.

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Desired fellow characteristics

I'm mentoring projects that apply AI advances to core biosecurity challenges — early detection and attribution of biological threats, characterizing AI-enabled bioweapons uplift, accelerating medical countermeasure design, and building biosecurity-by-design into frontier biological AI tools. Fellows have wide latitude to scope their own project within (or adjacent to) these themes, including ideas I haven't yet considered, and are expected to drive the technical work independently. My comparative advantage is high-level strategic direction grounded in biosecurity, pandemic preparedness, epidemiology, and US R&D policy rather than hands-on ML or software engineering guidance.

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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.