PhD position on Knowledge Graphs and LLMs for Decentralised Data Governance

The rapid growth of the data economy and the privacy implications accompanying it have motivated a new paradigm shift towards decentralisation of data on the Web, which aims to foster data sovereignty and empower individuals by allowing them to take back control over their data. However, the process of implementing data governance in a decentralised setting, especially when AI is involved, brings forth various socio-technical challenges related to data interoperability, process transparency, legal compliance (e.g. with GDPR, EU AI Act), privacy-preservation, and individuals’ trust and comprehension of decentralisation itself.

Details:

We are looking for an ambitious and motivated student with background in Computer Science or AI to undertake a 3 - 3.5 year fully funded PhD research project at the School of Computer Science, University of Birmingham. This scholarship covers (UK home) tuition fees and stipend. The stipend is the national UK standard.

We particularly encourage applications from students who have a background in ontologies, knowledge graphs and data privacy.

Person specification:

· MSc in Computer Science, AI or data science (minimum of 2:1 degree or higher)

· UK home student status holder

· Excellent oral and written communication skills in English

· Strong problem-solving abilities

· Interdisciplinary computer science interests

· Ability to work independently and in a collaborative environment

Essential skills:

· Experience with ontologies and knowledge graphs

· Experience with data privacy, data governance

Experience with generative AI (e.g. LLMs)

Desirable:

· Interest in Human-Computer Interaction

· Interest in privacy enhancing technologies (PETs)

· Familiarity with, or keen interest in, decentralised technology (e.g. SOLID, distributed ledgers)

Other:

· Experience in presenting or preparing scientific papers for journals and conferences is preferred but not essential

How to apply?

Please submit your (i) CV, (ii) motivational letter outlining why you are interested in the topic and your prior relevant experience, (iii) academic transcripts for consideration and (iv) a reference letter (e.g. from your MSc thesis supervisor) to [email protected].

DEADLINE: 3 September 2025

Shortlisted candidates will be invited to an interview and asked to give a presentation.

For more information, please contact the main supervisor of this project - Dr. Anelia Kurteva ([email protected]).