Northeastern University London | PhD Position in higher-order coordination and emergent communication across human, AI, and animal systems

The Project

How does the structure of group interactions shape coordination, norm formation, and the emergence of communication systems? What changes when we move from pairwise to genuinely group-level interactions — in human populations, in multi-agent AI systems, and in animal societies? Can the same mathematical framework describe convention formation in online human groups, the spontaneous emergence of language in AI agent populations, and the vocal traditions of sperm whales?

This research project, part of the ERC Consolidator Grant “RUNES” (Reconstruction and Unification of Neural and Ecological Systems), aims to investigate how higher-order interaction topology shapes collective outcomes across three classes of cognitive systems, employing an interdisciplinary approach that integrates online behavioural experiments, multiagent simulations, and the analysis of animal communication data.

Social coordination on group interaction structures: Extending the naming-game framework (Centola et al., Science 2018) from pairwise networks to higher-order interaction topologies, we will design and run large-scale online coordination experiments via Prolific, systematically varying group size, overlap, and clustering. The aim is to test how group-level interaction structure shifts tipping-point dynamics and convention formation, comparing against matched pairwise controls. By fitting higher-order contagion models and informationtheoretic decompositions to the experimental data, we will quantify the contributions of group interactions that pairwise models miss.

Emergent communication in multi-agent AI systems: We will investigate how interaction topology shapes the complexity and compositionality of communication protocols in multiagent systems. Building on recent work showing that LLM agent populations spontaneously develop shared social conventions through naming-game interactions, we will test whether convention formation dynamics on group topologies mirror those observed in human experiments. Reinforcement-learning agents in controlled environments will serve as a mechanistic validation layer, allowing us to isolate the effects of topology from agent architecture. Across both platforms, we will measure communication complexity using information-theoretic tools — synergy–redundancy decompositions, description-length measures — to enable direct cross-system comparison.

Animal communication and collective coordination: Using data from Project CETI (sperm whale vocalisations, tracking, and behavioural data from on-body tags) and from collaborating labs (zebrafish collective behaviour under multiple social conditions, with neural activity markers enabling proxy measures of functional coupling), we will apply higher-order statistical analysis to test whether group-level signatures in communication and coordination data predict collective outcomes — such as group spacing changes, behavioural synchrony, and leadership transitions — beyond what pairwise models capture. This builds on the PI’s prior work on social learning across symbolic cultural barriers in sperm whales (Leitao, Lucas, Poetto, Hersh, Gero, Gruber & Petri, eLife 2024).

The project will culminate in a cross-system synthesis, asking whether the topological and information-theoretic features that predict coordination in one system transfer to another — a foundational question for complex systems science.

The successful candidate will join the NP Lab within the Network Science Institute (led by Prof. G. Petri), and is expected to interact with members of the group, as well as with postdocs, graduate and PhD students, and to work across a range of applications of network science and complex systems, both within and outside of the lab.

Responsabilities

The successful candidates will:

• Have an MSc (or equivalent) in Physics, Mathematics, Computer Science, or a related quantitative field
• Have strong modelling, computational, and code development skills
• Have experience with network science, multi-agent systems, statistical mechanics, or computational social science
• Have good programming skills in at least one of: Python, Julia, Rust, C++
• Be excited and inspired by the proposed project area Be a self-starter with a highly collaborative spirit Have good communication skills
• Have an inquiring mind and be willing to challenge themselves

The successful candidates will benefit from a brand new campus on the banks of the River Thames next to Tower Bridge. This is an interdisciplinary, vibrant research environment with international collaboration and networking opportunities and dedicated research space. It will form the hub of a highly experienced, multi-institution supervisory team from NU London and the University of Kent.

Shortlisted candidates will be interviewed at the end of TBC. Candidates are welcome to contact the NU London supervisor with informal enquiries before the application deadline: Giovanni Petri (giovanni.petri@nulondon.ac.uk)

Supervisors

• Giovanni Petri (Network Science Institute, Northeastern University London)

• Zhongtian Sun (School of Computing, University of Kent) Aligned programme of study: PhD in Network Science Mode of study: Full-time

• Funding provider: Northeastern University London (NU London)
• Subject areas: Network Science, Computational Social Science, Collective Dynamics, Animal Communication
• Project start date: September 2026

Eligibility

Bachelor’s degree in a relevant subject - 2:1 or 1st (essential) Master’s degree in a relevant subject (optional)

IELTS 7 overall (with a score of at least 6.5 in each individual component) or equivalent. Nationality Applications are open to UK and international students. Please indicate if you are likely to require a visa on your application. We are unable to support visa costs

This scholarship covers the full cost of tuition fees, an annual stipend and an additional London allowance (set at UKRI rates) for 3.5 years.

How to Apply

Please send a CV, a 2-page Research Proposal related to the topics of the research project, and a Covering Letter stating how you meet the requirements and why you are interested in the proposed research project.

Application and more details: https://www.findaphd.com/phds/project/higher-order-coordination-and-emergent-communication-across-human-ai-and-animal-systems/?p196235