Constructor University
6 days ago
PhD in Knowledge Discovery from Unstructured Data to Shared Cognitive Maps Constructor University in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableCountry
Germany
University
Constructor University

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About this position
PhD opportunity in Computer Science, Artificial Intelligence, and Machine Learning at Constructor University (Bremen, Germany). The research group led by Prof. Dr. Andrey Ustyuzhanin, in collaboration with Constructor Knowledge Labs and Constructor Technology (industry partner), is inviting applications for a funded PhD project focused on knowledge discovery from unstructured data and the creation of shared cognitive maps.
The project aims to advance knowledge representation and adaptive reasoning systems. Research topics include transforming unstructured data into interactive knowledge graphs and personalized cognitive maps, designing interpretable and persistent knowledge structures, and addressing hierarchy, composability, and coarse-graining for robust task-specific reasoning. The work also explores individual and community-level knowledge modeling, including profile extraction from artifacts such as papers and courses, and cross-domain abstraction.
Eligibility highlights: applicants should hold a recognized MSc degree (or equivalent) in Computer Science, AI, ML, or a related field. Strong candidates with a BSc and exceptional performance may be considered for a fast-track PhD. Required experience includes a strong mathematical background, practical work with knowledge-graph or information retrieval systems, hands-on use of large language models (LLMs), publication record in AI/ML or related areas, documented research experience, and strong academic English writing skills.
Funding: the position is fully funded through a dedicated fellowship, including a monthly stipend of €1,650, a €100 monthly research-cost allowance, a €100 monthly health-insurance subsidy, and an optional €550 mini-job allowance for part-time work.
Application: applications are reviewed on a rolling basis for an expected start date in September 2026. Applicants should prepare a CV, academic transcripts, a detailed motivation letter, and two recommendation letters.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
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