{"slug": "arena-9-0-call-for-applicants", "title": "ARENA 9.0: Call for Applicants", "summary": "ARENA (Alignment Research Engineer Accelerator) announced its ninth iteration, a 4-5 week ML bootcamp focused on AI safety, running in-person at LISA in London from October 5 to November 6, 2026. Applications are due by July 12, 2026, and the program aims to equip participants with ML engineering skills for technical AI safety work, with alumni having joined organizations like Apollo Research, METR, and UK AISI.", "body_md": "We're excited to announce the ninth iteration of [ARENA](https://www.arena.education/) (Alignment Research Engineer Accelerator), a 4-5 week ML bootcamp with a focus on AI safety! Our mission is to provide talented individuals with the **ML engineering skills, community, and confidence** to contribute directly to technical AI safety. ARENA 9.0 will be running in-person from [LISA ](https://www.safeai.org.uk/)from **October 5th – November 6th, 2026** (the first week is an optional review of Neural Network Fundamentals).\n\n**Apply here** **to participate in ARENA 9.0**** before 11:59pm on Sunday July 12th, 2026 (anywhere on Earth).**\n\nARENA has been successfully run eight times, with alumni going on to become [MATS ](https://www.matsprogram.org/)scholars, [LASR ](https://www.lasrlabs.org/)participants and [Pivotal ](https://www.pivotal-research.org/fellowship)participants; AI safety engineers at [Apollo Research](https://www.apolloresearch.ai/), [METR](https://metr.org/), [UK AISI](https://www.aisi.gov.uk/), and even starting their own AI safety organisations!\n\nThis iteration will run from **October 5th – November 6th, 2026** (the first week is an optional review of Neural Network Fundamentals) at the [London Initiative for Safe AI (LISA)](https://www.safeai.org.uk/) in Shoreditch, London. LISA houses AI safety organisations (e.g., Apollo Research, BlueDot Impact, IAPS), several other AI safety researcher development programmes (e.g., LASR Labs, PIBBSS, Pivotal, Catalyze Impact, ILIAD), and many individual researchers (independent and externally affiliated).\n\nBeing situated at LISA brings several benefits to participants, such as productive discussions about AI safety research agendas, allowing participants to form a better picture of what working on AI safety can look like in practice, and offering chances for research collaborations post-ARENA.\n\nThe main goals of ARENA are to:\n\nThe programme's structure will remain broadly the same as ARENA 8.0. For more information on the structure of ARENA, [see our website](http://arena.education/) (soon to be updated with our new material). You can look at the ARENA materials [ here](https://learn.arena.education/).\n\nAlso, please note that we have a Slack group designed to support the independent study of the material ([ join link here](https://info-arena.github.io/ARENA_img/slack.html)).\n\nThe 4-5 week programme will be structured as follows:\n\nBefore getting into more advanced topics, we first cover the basics of deep learning, including basic machine learning terminology, what neural networks are, and how to train them. We will also cover some subjects we expect to be useful going forward, e.g. using GPT-3 and 4 to streamline your learning, good coding practices, and version control.\n\n**Note:** Participants can optionally skip this week of the programme and join us at the start of week 1 if:\n\nIt is recommended that participants attend, even if they’re familiar with the fundamentals of deep learning.\n\nTopics include:\n\nThis week, you will learn all about transformers and build and train your own. You'll also study LLM interpretability, a field which has been advanced by Anthropic’s [Transformer Circuits sequence](https://transformer-circuits.pub/), and work by Neel Nanda and the Google DeepMind Interpretability Team. This week will also branch into areas more accurately classed as 'alignment science' than interpretability, for example, work on token-level analysis of reasoning models, and model organisms of misalignment.\n\nTopics include:\n\nThis week, you will learn about some of the fundamentals of RL and work with OpenAI’s Gym environment to run their own experiments.\n\nTopics include:\n\nThis week, you will learn how to evaluate models. We'll take you through the process of building a multiple-choice benchmark of your own and using this to evaluate current models through UK AISI's [Inspect ](https://inspect.aisi.org.uk/)library. We'll then move on to study LM agents: how to build them and how to elicit behaviour from them. We'll also have the option for participants to explore beyond evals, and study some of the methods used in AI control.\n\nTopics include:\n\nWe will conclude this program with a Capstone Project, where participants will receive guidance and mentorship to undertake a 1-week research project building on materials taught in this course. This should draw on the skills and knowledge that participants have developed from previous weeks and our paper replication tutorials.\n\n[Here](https://colab.research.google.com/github/callummcdougall/ARENA_3.0/blob/main/chapter1_transformer_interp/exercises/part41_indirect_object_identification/1.4.1_Indirect_Object_Identification_exercises.ipynb?t=20250127) is some sample material from the course on how to replicate the [Indirect Object Identification paper](https://arxiv.org/abs/2211.00593) (from the week on Transformers & Mechanistic Interpretability). An example Capstone Project might be to apply this method to interpret other circuits, or to improve the method of path patching. You can see some examples of capstone projects from previous ARENA participants [here](https://www.arena.education/previous-capstone-projects), as well as posts on LessWrong [here ](https://www.lesswrong.com/posts/f9cnGHCiJgo5eDkSQ/understanding-reasoning-with-thought-anchors-and-probes)and [here](https://www.lesswrong.com/posts/wxPvdBwWeaneAsWRB/the-self-hating-attention-head-a-deep-dive-in-gpt-2-1).\n\nARENA has been successful because we had some of the best in the field TA-ing with us and consulting with us on curriculum design. If you have particular expertise in topics in our curriculum and want to apply to be a TA, [ use this form to apply](https://airtable.com/appZIMMH3ywSxS0A9/pagQnSXhjbrsEaCNx/form). TAs will be well compensated for their time. Please contact\n\nA: There’s no single profile that we look for at ARENA; in recent iterations, successful applicants have come from diverse academic and professional backgrounds. We intend to keep it this way – this diversity makes our bootcamps a more enriching learning experience for all.\n\nWhen assessing applications to our programme, we like to see:\n\nSince ARENA is an ML bootcamp, some level of technical skill in maths and coding will be required – more detail on this can be found in our [FAQs](https://www.arena.education/faqs). However, if our work resonates with you, we encourage you to apply.\n\nAt the start of the programme, most days will involve **pair programming**, **working through structured exercises designed to cover all the essential material in a particular week**. The purpose is to get you more familiar with the material in a hands-on way. There will also usually be a short selection of required readings designed to inform the coding exercises.\n\nAs we move through the course, some weeks will transition into more open-ended material. For example, in the Transformers and Mechanistic Interpretability week, after you complete the core exercises, you'll be able to choose from a large set of different exercises, covering topics as broad as model editing, superposition, circuit discovery, grokking, discovering latent knowledge, and more. In the last week, you'll choose a research paper related to the content we've covered so far & replicate its results (possibly even extend them!). There will still be TA supervision during these sections, but the goal is for you to develop your own research & implementation skills. Although we strongly encourage paper replication during this week, we would also be willing to support well-scoped projects if participants are excited about them.\n\nWe're expecting to accept around 30 participants in the in-person programme.\n\nA: Yes, we will send you prerequisite reading & exercises covering material such as PyTorch, einops and some linear algebra a few weeks before the start of the programme. This should take about 8 hours to complete.\n\nA: The deadline for [ submitting applications](https://airtable.com/appZIMMH3ywSxS0A9/pagnvd5oNoOjApQQN/form) is\n\nA: There will be three steps:\n\nA: Participants will be expected to attend the entire programme. The material is interconnected, so missing content would lead to a disjointed experience. We have limited space and, therefore, are more excited about offering spots to participants who can attend the entirety of the programme.\n\nThe exception to this is the first week, which participants can choose to opt in or out of based on their level of prior experience (although attendance is strongly recommended if possible).\n\nA: We won't pay stipends to participants. However, we will be providing housing, food and travel assistance to our participants (see below). We aim to ensure that finances do not present a barrier to any candidates participating in ARENA.\n\nA: We will cover all travel expenses to and from London (which will vary depending on where the participant is from) and expenses incurred in acquiring a travel visa, where needed. Accommodation, meals, and drinks and snacks will also all be included during the duration of the programme.\n\nA: If either of these is the case, please feel free to reach out directly via an email to [info@arena.education](mailto:info@arena.education) (alternatively, send [JamesH ](https://www.lesswrong.com/users/atlasofcharts)a message in the ARENA slack, or on LessWrong). We'd love to hear from you!\n\n[ Here is the link to apply as a participant.](https://airtable.com/appZIMMH3ywSxS0A9/pagnvd5oNoOjApQQN/form) We expect it to take no more than 90 minutes.\n\n[ Here is the link to apply as a TA.](https://airtable.com/appZIMMH3ywSxS0A9/pagQnSXhjbrsEaCNx/form) You shouldn't spend longer than 30 minutes on it.\n\nWe look forward to receiving your application!", "url": "https://wpnews.pro/news/arena-9-0-call-for-applicants", "canonical_source": "https://www.lesswrong.com/posts/y795kpdRqC3uRmhtt/arena-9-0-call-for-applicants", "published_at": "2026-06-25 15:32:17+00:00", "updated_at": "2026-06-25 15:45:44.905770+00:00", "lang": "en", "topics": ["ai-safety", "machine-learning", "ai-research"], "entities": ["ARENA", "LISA", "Apollo Research", "METR", "UK AISI", "Anthropic", "Google DeepMind", "OpenAI"], "alternates": {"html": "https://wpnews.pro/news/arena-9-0-call-for-applicants", "markdown": "https://wpnews.pro/news/arena-9-0-call-for-applicants.md", "text": "https://wpnews.pro/news/arena-9-0-call-for-applicants.txt", "jsonld": "https://wpnews.pro/news/arena-9-0-call-for-applicants.jsonld"}}