Princint x ILLIAD Research residency 2026

2026-01-02 — 2026-01-02

Wherein a research residency is presented, hosted in London at the London Initiative for Safe AI for researchers in mathematics or physics to work on AI alignment, and an invitation to connect is extended.

machine learning
neural nets
AI safety
Figure 1

I am part of the inaugural cohort of the Principles of Intelligence Research Residency from January to February 2026.

TL;DR: PIBBSS and Iliad are announcing a Research Residency in applied mathematics and AI alignment. Competitive candidates are PhD or postdoctoral (or equally experienced) researchers in math, physics, or a related field. Our target outcome is for Researchers-in-Residence to continue research after the Residency by securing philanthropic funding to either start new research groups or to support other research projects.

This should be fun.

Hit me up if you’re in London. We’ll be based at the London Initiative for Safe AI, which looks to be centrally located.

1 References

Demirtas, Halverson, Maiti, et al. 2023. “Neural Network Field Theories: Non-Gaussianity, Actions, and Locality.”
Garrabrant, Benson-Tilsen, Critch, et al. 2020. “Logical Induction.”
Meulemans, Nasser, Wołczyk, et al. 2025. “Embedded Universal Predictive Intelligence: A Coherent Framework for Multi-Agent Learning.”
Ngo, Chan, and Mindermann. 2024. “The Alignment Problem from a Deep Learning Perspective.”
Sadek, Farrugia-Roberts, Anwar, et al. 2025. “Mitigating Goal Misgeneralization via Minimax Regret.”
Vereshchagin, and Shen. 2015. “Algorithmic Statistics Revisited.”