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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
Machine Learning
*
Artificial intelligence
*
Large Language Models (LLMs)
*
Data Science
*
* Required skills
Benefits
Monthly stipend of €1,650
Supplementary €550 mini-job allowance for optional part-time employment
Monthly research-cost allowance of €100
Health-insurance subsidy of €100 per month
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