PhD in Knowledge Discovery

About This Role

This PhD position focuses on knowledge discovery, transforming unstructured data into actionable knowledge, and envisioning intelligent systems. It aims to develop innovative frameworks for knowledge representation and adaptive reasoning within the fields of AI, Machine Learning, and information systems.

Responsibilities

• Transform unstructured data into interactive knowledge graphs and personalized cognitive maps
• Design interpretable, persistent, and navigable knowledge structures
• Address challenges such as hierarchy, composability, and coarse-graining for robust, task-specific reasoning
• Explore individual and community-level knowledge modeling, including personalized domain maps and profile extraction from artifacts
• Enable cross-domain abstraction to support knowledge transfer and collaboration

Requirements

• Recognized MSc degree (or equivalent) in Computer Science, Artificial Intelligence, Machine Learning, or a closely related discipline
• Strong mathematical background
• Experience in defining and developing knowledge-graph or information retrieval systems
• Practical experience with large language models (LLMs) and their applications
• Track record of publications in AI/ML or related areas
• Documented experience in practical research work
• Strong academic English writing skills

Qualifications

• MSc degree (or equivalent) in Computer Science, Artificial Intelligence, Machine Learning, or a closely related discipline

Skills

* Required skills

Benefits