FREE PhD study and funding virtual fair REGISTER NOW FREE PhD study and funding virtual fair REGISTER NOW

Artificial Intelligence, Gender and Political Violence


   Centre for Accountable, Responsible and Transparent AI

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
  Prof H Coffé, Dr Tom Fincham Haines, Dr Özgür Şimşek  Applications accepted all year round  Competition Funded PhD Project (UK Students Only)

About the Project

Political violence is an important issue. It affects personal integrity of individuals, and political integrity, decreases democratic quality, and undermines the fairness of the political process. Therefore, it is important to study and to understand when, where and how political violence occurs. The current project will focus in particular on online political violence which has - together with the growth of online (social) media - increased. As such, it will also move beyond the traditional focus of studies on political violence on physical assault, mostly in conflict settings or regimes in transition. In particular, it will define online political violence as any online reaction or comment that violates the personal integrity of individuals involved in the political process and focus on Western post-industrialised societies, including the UK.

Bringing insights from mathematics and computer science into the study of online political violence, the project aims to (1) use political science concepts to examine how far, and how, men and women are targeted differently online; (2) develop artificial intelligence techniques for detecting and predicting the presence, spread, and escalation of online political violence; (3) to develop these insights to prevent the presence, spread, and escalation of online political violence. Throughout the project, a gendered perspective will be taken, as previous research – mostly focusing on physical violence – has suggested that women, and in particular more powerful and visible women, tend to experience more political violence than men. 

To identify and model the dynamics of online political violence, detection, classification and regressing escalation with natural language processing will be used. In addition, interactions with the news media will be modelled using Bayesian techniques, in particular graphical models. Reinforcement learning (sequential decision making) will be used to model the behaviour of the agents over time and explore prevention.

This project is associated with the UKRI Centre for Doctoral Training (CDT) in Accountable, Responsible and Transparent AI (ART-AI). We value people from different life experiences with a passion for research. The CDT's mission is to graduate diverse specialists with perspectives who can go out in the world and make a difference.

Applicants should hold, or expect to receive, a first or upper-second class honours degree in computer science, mathematics, statistics, engineering, social sciences, policy research, psychology, or a related subject. An interest in politics/political science is desirable. Applicants should have taken a mathematics unit or a quantitative methods course at university or have at least grade B in A level maths or international equivalent.

Informal enquiries about the research should be directed to Prof Hilde Coffé.

Formal applications should be accompanied by a research proposal and made via the University of Bath’s online application form. Enquiries about the application process should be sent to .

Start date: 3 October 2022.


Funding Notes

ART-AI CDT studentships are available on a competition basis and applicants are advised to apply early as offers are made from January onwards. Funding will cover tuition fees and maintenance at the UKRI doctoral stipend rate (£16,062 per annum in 2022/23, increased annually in line with the GDP deflator) for up to 4 years.
We also welcome applications from candidates who can source their own funding.
Search Suggestions
Search suggestions

Based on your current searches we recommend the following search filters.

PhD saved successfully
View saved PhDs