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Safe AI Netherlands

Make a first real contribution to AI Safety

The SAIN Project Hub matches you with an experienced supervisor, arranges compute, and takes a project from open question to published finding. It is voluntary, remote-friendly, and open for applications at any time.

Apply for a projectRead the handbookBrowse open projects

Find a project, then join it

Each project here was offered by a SAIN supervisor and is described in their own words. One application form covers all of them: name up to three projects in it, and the projects team will introduce you to the supervisors within a working week. A VU or UvA thesis counts towards a degree there, so it is for that university’s students; every other project is open to anyone with the right background.

Apply for a project

32 projects from 12 supervisors

  • VU thesis: VU students only

    SocietalEvaluations

    Filip IlievskiAssistant Professor, VU Amsterdam

    Study how short, multimodal media shape what people believe about AI's harms and benefits, combining social-science frameworks with current AI modelling.

  • Open to everyone

    Formal methodsAlignment and RL

    Satchit ChatterjiPhD candidate, University of Amsterdam

    Use formal guarantees, symbolic reasoning or structured representations to make machine learning systems safer, in general-purpose or expert systems, from foundational methods to applied work.

  • Open to everyone

    Evaluations

    Sandro PezzelleAssistant Professor, University of Amsterdam

    Measure how well current VLMs understand and narrate visual events, and whether human behavioural and cognitive patterns can improve them.

  • Open to everyone

    InterpretabilityFormal methods

    Fausto CarcassiAssistant Professor, University of AmsterdamLimited: 1 place left across his projects

    Apply program synthesis to automate building models of how LLMs implement computations.

  • Open to everyone

    InterpretabilityEvaluations

    Leon EshuijsPhD student, VU Amsterdam

    Build evaluations or use interpretability methods to study behaviours such as sycophancy, or how models analyse user characteristics when they respond.

  • Open to everyone

    Security and privacy

    Fatih TurkmenAssociate Professor, University of Groningen

    Find and fix security and privacy problems in large language models and retrieval-augmented generation.

You do not need a university post to do this work

SAIN’s offer is one line: bring your expertise to AI Safety, and the community, supervision, and support are here to take it further. The rest of this page is the mechanism behind that line: how a project is chosen, what support looks like week to week, and where the work ends up.

The hub is open to anyone with sufficient background:

  • Students at Bachelor, Master, or PhD level
  • Researchers, and people working in industry
  • Policy professionals
  • People with no formal affiliation

Remote participation works. Applications are rolling, so you can apply whenever you are ready, and for supervised projects you hear back within a working week.

One thing the hub is not: a job. SAIN does not pay stipends or salaries; participation is voluntary and educational. What SAIN does provide is supervision, compute, coordination, and, within reason, help with conference travel.

From open question to published finding

Every project in the hub moves through the same three steps. The handbook spells each one out in full; this is the shape of it.

  1. Choose a project

    There are three ways in, and all three are normal.

    1. Join a supervisor's project. Every project a SAIN supervisor has offered is listed at the top of this page. Find one that fits your background and register your interest; the projects team introduces you to the supervisor.

    2. Join an open collaboration. Some projects run without formal supervision. One person leads, usually whoever designed the project, and SAIN connects collaborators and supports the work.

    3. Bring your own idea. Write a short proposal: the question, why it matters, how you would test it, and what you need. SAIN's Project Team reviews it, and can help you shape it if it is not fully formed yet.

    Not every valuable contribution is a research paper: the work can be technical, governance, policy, or conceptual. When choosing projects, the team looks at three things: relevance to the Netherlands and Europe, relevance to transformative AI, and whether it can succeed on a small budget. If you are unsure whether a topic counts as AI Safety, the default answer is yes, provided you can articulate a plausible pathway from the work to reducing risk from transformative AI.

    Read the Project Hub handbook

  2. Work with support

    Fill in the application form and, for supervised projects, you hear back within a working week. If there is a fit, a supervisor is formally assigned and the project gets its own channel in the community.

    Supervision is a working relationship, not a lecture. You drive the day-to-day work; your supervisor helps scope the project realistically, reviews experiments and drafts, and steps in when a direction stops being productive. Meetings run weekly or biweekly, and you agree your commitment per project up front, whether that is five to ten hours a week alongside a degree or something closer to full time.

    Supervisors come from universities, industry, and government. In academia they are usually at PhD level or more senior; outside it, they have several years of senior experience in a relevant role. Compute is arranged per project at the start, and computationally inexpensive projects are encouraged. Remote participation works throughout.

    Meet the supervisors

  3. Publish your findings

    A project is complete when its main question is adequately answered, including when the answer is negative, and the result is published in a presentable form: a paper, a policy brief, an evaluation or open-source tool, or a blog post on SAIN’s Substack or LessWrong. You get feedback on drafts, and SAIN may help with conference travel within reason.

    That is not hypothetical. Work from this community has been accepted at workshops at NeurIPS and ICLR, which is where most first contributions in this field land.

    NeurIPS 2025 workshop · Spotlight

    The Anatomy of Alignment: Decomposing Preference Optimization by Steering Sparse Features

    A transparent view of preference optimisation reveals how models can learn to favour style and formatting over honesty.

    Read paper

    ICLR 2025 · Building Trust Workshop

    Self-Ablating Transformers: More Interpretability, Less Sparsity

    Training small language models to select their active components produces more specialised, interpretable circuits without sacrificing language modelling performance.

    Read paper

    NeurIPS 2025 · Regulatable ML Workshop

    EU-Agent-Bench: Measuring Illegal Behavior of LLM Agents Under EU Law

    A benchmark tests whether AI agents take unlawful actions under EU law, even when the user’s request is benign.

    Read paper

The people you would work with

Every supervisor keeps a public agenda of the projects they would like to supervise. Read it before you apply: the strongest expressions of interest respond to a question a supervisor has already posed.

Supervise the next project

If you have substantial experience in a relevant field, usually PhD level or above in academia or several years in a senior role in industry or policy, and the work above looks like something you could guide, more supervisors means more projects. You do not need to be an AI Safety expert already. Supervision is remote-friendly, meetings run at a cadence you agree per project, and the Project Team handles the coordination around you. Fill in the supervisor form and we will follow up with next steps.

Become a supervisor (opens in a new tab)

Apply whenever you are ready

Applications are rolling, and for supervised projects you hear back within a working week. Fill in the application form, or email the projects team if you are not sure where you fit and we will help route you.

Apply for a projectEmail the projects team

The full process, expectations, and norms are written down. Read the Project Hub handbook