This track is for prospective founders, field-builders, high-agency generalists, and general managers who want to launch new AI safety initiatives. Over 12 weeks (with a potential 6–12 month extension), fellows build and launch something new with weekly guidance from mentors (founders, field-builders, sitting CEOs, program directors, etc.) who have done it themselves.
We think AI safety needs to scale fast to ensure AI development and deployment goes well. At MATS, we are proud to have trained 10 cohorts of top researchers, but high-impact organizations are increasingly bottlenecked by management and scaling. There are more promising ideas than there are “general managers” to champion them, and available funding and capital are outpacing the capacity for deployment. We are launching the MATS Founding & Field-Building track to solve these bottlenecks and scale AI safety.
We want fellows who are resourceful, principled, and motivated to do work that matters. There are three main pathways in this track:
If you see yourself in any of these roles, we want you to apply!
Potential project inspiration from: Coefficient Giving 2025 Technical AI Safety RFP, Bio Action Plan, Lizka Vaintrob & Owen Cotton-Barratt, Eric Ho, Marius Hobbhahn, Julian Hazell, Abbey Chaver, and Asya Bergal.
Founding ambitious AI safety and field-building projects.
Minimum support = 2x 30-min meetings per week. We could scale this up as appropriate.
I'll be based in SF. If the fellows want to work in BlueDot's office for some periods of time, I could collaborate with them daily.
I'm available for quick calls anytime, and am responsive on Slack.
I'm open to people with a wide range of backgrounds. Though you need to be willing to work very hard, be great at communicating, and have a burning desire to make AI go well.
I work best with people who are intense, communicate and reason clearly, and are mission-driven.
We'll work together to design the project. You'll have a lot of freedom to figure out what the best shape of thing to do is, and I'll provide lots of regular feedback and make relevant introductions to help you refine the proposal.
Your first 1-2 weeks will be focused on figuring out what to do, and the rest of the fellowship will be focused on execution.
This stream will focus on biosecurity, behavioral science for AI governance, and evaluating interventions to reduce catastrophic risk.
Eleos AI Research is a nonprofit working to ensure the interests of AI systems are appropriately taken into account as we navigate transformative AI. We are looking for competent generalists to help scale up our AI welfare field-building by running high-impact events, or to otherwise amplify our research, communications, and operational capacity.
By default, I expect to meet with each fellow for at least 60 minutes per week (possibly split into 2 x 30 minute meetings). For projects that require a lot of input (e.g. event organizing), we can scale that up as needed. I’ll also be available for ad hoc meetings, and can be reached asynchronously on Slack or by email. At Eleos, we each post a daily update in Slack; I would like fellows to do the same.
The ideal candidate:
We'll meet at the start of the program to discuss ideas in the areas listed above, as well as ideas that fellows would like to pitch. We’ll jointly decide on a project that aligns with Eleos’s priorities as well as the goals and skills of the fellow.
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.
Co-mentorship from Halcyon's Ross Matican (Investor & Grantmaker), Mike McCormick (Founder, CEO), and Charlie Petty (Venture Partner). Ross will be leading point.
Scheduled 45 min bi-weekly meetings (every other week). Ad hoc meetings can be added between scheduled sessions. We'll have a shared Slack channel with Ross, Mike, and Charlie, as well as the supporting team at Halcyon. Ping us anytime.
For product development and organization building projects:
For generalist projects:
For product development and organization building projects in the areas of AI safety and alignment, biosecurity, and critical cybersecurity - fellows will have full freedom. We expect fellows to come with rough ideas and opinions on direction that will inform where they start exploring the market. We don’t expect refined ideas or pitches. We do expect building.
For field building and generalist fellows, we are prioritizing a talent matching project. This includes processing thousands of individuals in our CRM, and finding how they may pair with our portfolio companies and other areas of high priority in our network.
The MATS Program is a 10-week research fellowship designed to train and support emerging researchers working on AI alignment, transparency and security. Fellows collaborate with world-class mentors, receive dedicated research management support, and join a vibrant community in Berkeley focused on advancing safe and reliable AI. The program provides the structure, resources, and mentorship needed to produce impactful research and launch long-term careers in AI safety.
MATS mentors are leading researchers from a broad range of AI safety, alignment, governance, field-building and security domains. They include academics, industry researchers, and independent experts who guide scholars through research projects, provide feedback, and help shape each scholar’s growth as a researcher. The mentors represent expertise in areas such as:
Key dates
Application:
The main program will then run from September 28th to December 4th, with the extension phase for accepted fellows beginning in December.
MATS accepts applicants from diverse academic and professional backgrounds - from machine learning, mathematics, and computer science to policy, economics, physics, cognitive science, biology, and public health, as well as founders, operators, and field-builders without traditional research backgrounds. The primary requirements are strong motivation to contribute to AI safety and evidence of technical aptitude, research potential, or relevant operational experience. Prior AI safety experience is helpful but not required.
Applicants submit a general application, applying to various tracks (Empirical, Theory, Strategy & Forecasting, Policy & Governance, Systems Security, Biosecurity, Founding & Field-Building.
In stage 2, applicants apply to streams within those tracks as well as completing track specific evaluations.
After a centralized review period, applicants who are advanced will then undergo additional evaluations depending on the preferences of the streams they've applied to before doing final interviews and receiving offers.
For more information on how to get into MATS, please look at this page.