Your day will typically begin at our co-working space located in Harvard Square, where you’ll dive into your research project. Around lunchtime, you will attend the weekly speaker event series with virtual or in-person guests. Afternoons usually involve dedicated deep-work sessions focused on your individual research projects. In the evenings, fellows frequently gather for dinner, followed by various group activities, ranging from paper reading groups to board game nights.

Throughout the week, you'll also have scheduled one-on-one check-ins with your research manager, members of the CBAI team, and coffee chats with other fellows, as well as numerous opportunities to engage with other fellowship events.

Fellows are expected to produce written outputs suitable for sharing publicly. These could be in the form of blog posts, interactive demos (if applicable), pre-prints, and paper submissions to ICLR, ICML, and NeurIPS.

While there are no rigid guidelines concerning the format or scope of these outputs, we will actively support fellows by identifying relevant conference opportunities, such as NeurIPS, and assisting them in showcasing their research to broader AI safety and academic communities.

We anticipate this fellowship will lead to ongoing mentorship relationships and foster new collaborations among fellows, providing a foundation for continued engagement and future joint projects.

We will organize a speaker series with renowned researchers and peer researchers in the Cambridge area to expose you to frontier research and other relevant research areas that you might be interested in pursuing post-fellowship.

We will organize a range of engaging activities, including networking opportunities with researchers in the CBAI network, research workshops, and wargames.

Additionally, you'll have opportunities to interact regularly with AI safety researchers from institutions such as Harvard and MIT through MAIA and AISST, AI safety student groups that are fiscally sponsored and operated by CBAI.

While CBAI fiscally sponsors and operates the AI Safety Student Team at Harvard and MIT AI Alignment, we are not officially affiliated with Harvard or MIT. Therefore, fellows will not receive student identification cards.

Note: If you are a student at a university affiliated with BorrowDirect, you are eligible for a library card granting access to the libraries at Harvard and MIT.

We will do our best to arrange a housing option for you for the entire program. This will most likely be in the form of sharing a house with other fellows.

If you prefer not to share a house, please reach out to us, and we may be able to provide housing reimbursement (capped and contingent on adequate proof of payment).

Mentor matching is a key component of our program, ensuring each fellow receives dedicated support and guidance. Therefore, if no mentor selects you during the matching process, we will not be able to offer you a place in the CBAI Spring Research Fellowship.

Our default expectation is that all fellows participate in person for the full duration of the fellowship.

However, we understand there may be special circumstances, and we are open to evaluating these on a case-by-case basis. Please indicate clearly in your application if you anticipate needing to attend only part of the program in person.

Successful applicants typically demonstrate clear alignment with the goals and values of our program, a well-articulated interest in AI safety, strong motivation for pursuing research in this area, and a (clear) goal/plan for the post-fellowship.

To strengthen your application, clearly outline your relevant background, skills, and past experiences, explain specifically why you're interested in this fellowship, and highlight the impact you hope to achieve through your participation.

Your research manager will provide ongoing support in project management, help track your research progress, and may also offer research-specific guidance depending on their expertise.

In contrast, your mentor is an external expert specifically matched to your research area, providing specialized domain knowledge, targeted advice, and influencing the research direction.