PhD Studentship: Knowledge Graphs and LLMs for Decentralised Data Governance

University of Birmingham; Birmingham; On-site; GBP 80,000 - 100,000; Full time

Job summary

A leading research university in Birmingham seeks an ambitious student for a fully funded PhD project in Computer Science. The research focuses on decentralised personal data governance using multimodal knowledge graphs and AI. Candidates should have a strong background in computer science or AI, excellent communication skills, and a keen interest in data privacy and governance. This position offers tuition fees and a stipend at the national UK standard.

Benefits

Fully funded tuition fees

Stipend at national standard

Qualifications

• Excellent oral and written communication skills in English.
• Strong problem-solving abilities.
• Ability to work independently and in a collaborative environment.

Responsibilities

• Investigate necessary data infrastructure for decentralised governance.
• Explore how multimodal knowledge graphs and AI can assist in data governance.
• Support individuals in understanding and managing their decentralised data.

Skills

Experience with ontologies and knowledge graphs

Experience with data privacy and interest in data governance

Familiarity with decentralised technology

Education

MSc in Computer Science or AI (minimum of 2:1)

Job description

Overview

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. This project aims to address key questions related to: infrastructure, technology and user empowerment.

Expected outcomes: A novel approach combining multimodal knowledge graphs, LLMs and visualisations to support individuals with their decentralised personal data governance. Raised awareness of data privacy and trust in AI and decentralisation. Scientific paper(s) publication at top tier ranked international conferences and journals in Computer Science.

Responsiblities / Research Questions

• Infrastructure: What data infrastructure is needed to enable the robust and efficient implementation of decentralised personal data governance frameworks?
• Technology: How can multimodal knowledge graphs in combination with generative AI help individuals govern their data (e.g. within decentralised contexts)?
• User Empowerment: How to support individuals in making sense of their decentralised data and its governance? Can visualisations help?

Person specification

• MSc in Computer Science or AI (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 and interest in data governance
• Familiarity with, or keen interest in, decentralised technology (e.g. SOLID, distributed ledgers)

Desirable

• Experience with generative AI (e.g. LLMs)
• Interest in Human-Computer Interaction
• Interest in privacy enhancing technologies (PETs)

Other

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

Funding notes

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.

References

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