Advanced AI could go badly wrong for humanity. Pivotal exists to lower that risk. We try to find the strongest new researchers and put them to work on it with experienced mentors in our fellowship.
TL;DR:
15 weeks of funded, full-time AI safety research in London (January 18 - April 30, 2027), with everything you need to make your research go well: a dedicated mentor, a Research Manager, budget for food/housing/compute/travel, and a healthy £15-18k stipend.
Projects span technical safety, technical governance and AI governance. Apply by 23:59 Sunday November 1 (AoE). Apply here.
For 15 weeks, fellows work in person at LISA on a research project with an external mentor. Each fellow gets weekly 1:1s with their mentor, weekly support from a Pivotal Research Manager, who helps with scoping, blockers, and career planning, and a cohort of ~40 peers working on adjacent problems. Our last 4 cohorts received an average peer recommendation of 9.0/10, and an average satisfaction of 8.7/10.
Fellows already rate the program highly but we’ve made Pivotal bigger and hopefully better this time around: we’ve extended our original 9-week format to 15-weeks, increased our housing stipend to £1,800 per month, and increased our fellow stipend to £15-18k (depending on seniority). You now have more time to scope, run, and write the output a full project, more compute for more ambitious projects, and more breathing room to invest in career development.
At the end of the 15 weeks, the goal is for you to have (a) published a research output, and (b) have concrete next steps lined up for your career.
We’ve deprioritised extensions, because we want you to start working outside of a fellowship as soon as possible.
Anyone that’s serious about contributing to AI going well should consider applying. Past fellows have ranged from first-year undergraduates to PhDs to experienced professionals without university degrees. In our experience, a strong match with a specific mentor often matters more than your overall background. We have mentors in technical safety, technical governance and AI governance.
Browse the mentor list to see whether we’re supporting research you’d be excited to work on.
After your fellowship
Across 8 cohorts and ~160 alumni, fellows have gone on to work at UK AISI, Geodesic, GovAI, METR, Apollo Research, SaferAI, DeepMind, IAPS, AI Futures Project, Timaeus, Cooperative AI Foundation, and elsewhere. A handful have founded or are founding organizations: Principia, PRISM Evals, Catalyze Impact, Moirai, and more coming soon.
Outputs are typically a paper or policy brief, with blog posts and other formats also common. Fellows retain ownership of their research. You can see projects from our last cohorts and a selection of past research outputs.
In the past few weeks alone we’ve had many NeurIPS 2026 acceptances, alumni quoted as experts in NPR's reporting on third-party AI evaluators, and a recent fellow joined METR's chain-of-thought monitorability team.
Should you apply?
If you’re reading this and want a research or policy career in AI safety, probably yes. Acceptance rates at programs like are in the 1-3% range. That sounds intimidating, but it shouldn’t drive most of your decision – readers of this site typically have severely increased chances.
If your interests and background seem like a plausible fit, applying is usually worth it.
How long it takes:
Main form: about an hour for most people.
Each mentor-specific application: about 20 minutes per mentor. You can come back later to apply to more mentors.
Advanced AI could go badly wrong for humanity. Pivotal exists to lower that risk. We try to find the strongest new researchers and put them to work on it with experienced mentors in our fellowship.
TL;DR:
Projects span technical safety, technical governance and AI governance. Apply by 23:59 Sunday November 1 (AoE). Apply here.
Know someone who might be a good fit? If you refer someone who gets accepted because of you, you’ll earn $1,000.
What the fellowship is
For 15 weeks, fellows work in person at LISA on a research project with an external mentor. Each fellow gets weekly 1:1s with their mentor, weekly support from a Pivotal Research Manager, who helps with scoping, blockers, and career planning, and a cohort of ~40 peers working on adjacent problems. Our last 4 cohorts received an average peer recommendation of 9.0/10, and an average satisfaction of 8.7/10.
Fellows already rate the program highly but we’ve made Pivotal bigger and hopefully better this time around: we’ve extended our original 9-week format to 15-weeks, increased our housing stipend to £1,800 per month, and increased our fellow stipend to £15-18k (depending on seniority). You now have more time to scope, run, and write the output a full project, more compute for more ambitious projects, and more breathing room to invest in career development.
At the end of the 15 weeks, the goal is for you to have (a) published a research output, and (b) have concrete next steps lined up for your career.
We’ve deprioritised extensions, because we want you to start working outside of a fellowship as soon as possible.
Anyone that’s serious about contributing to AI going well should consider applying. Past fellows have ranged from first-year undergraduates to PhDs to experienced professionals without university degrees. In our experience, a strong match with a specific mentor often matters more than your overall background. We have mentors in technical safety, technical governance and AI governance.
Browse the mentor list to see whether we’re supporting research you’d be excited to work on.
After your fellowship
Across 8 cohorts and ~160 alumni, fellows have gone on to work at UK AISI, Geodesic, GovAI, METR, Apollo Research, SaferAI, DeepMind, IAPS, AI Futures Project, Timaeus, Cooperative AI Foundation, and elsewhere. A handful have founded or are founding organizations: Principia, PRISM Evals, Catalyze Impact, Moirai, and more coming soon.
Outputs are typically a paper or policy brief, with blog posts and other formats also common. Fellows retain ownership of their research. You can see projects from our last cohorts and a selection of past research outputs.
In the past few weeks alone we’ve had many NeurIPS 2026 acceptances, alumni quoted as experts in NPR's reporting on third-party AI evaluators, and a recent fellow joined METR's chain-of-thought monitorability team.
Should you apply?
If you’re reading this and want a research or policy career in AI safety, probably yes. Acceptance rates at programs like are in the 1-3% range. That sounds intimidating, but it shouldn’t drive most of your decision – readers of this site typically have severely increased chances.
If your interests and background seem like a plausible fit, applying is usually worth it.
How long it takes:
Apply
Apply by November 1st. If you know someone who'd be a great fit, recommending them earns you $1,000.
Happy to answer questions in the comments.