Ph.D. Researcher. Knowledge Discovery: From Unstructured Data to Shared Cognitive Maps

Constructor Knowledge Labs
Bremen, Germany
7 days ago

Role details

Contract type
Permanent contract
Employment type
Part-time (≤ 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Bremen, Germany

Tech stack

Artificial Intelligence
Information Retrieval
Machine Learning
Unstructured Data
Large Language Models
Knowledge Representation
Information Technology

Job description

  • Transforming unstructured data into interactive knowledge graphs and personalized cognitive maps.
  • Designing models that provide interpretable, persistent, and navigable structures of knowledge.
  • Addressing challenges such as hierarchy, composability, and coarse-graining for robust, task-specific reasoning.
  • Exploring individual and community-level knowledge modeling, including personalized domain maps, profile extraction from artifacts (e.g., papers, courses), and cross-domain abstraction.

The overarching goal is to create systems that enable transparent, adaptive, and spatially intuitive representations of knowledge, supporting both individual users and collaborative communities., The appointment provides full financial coverage through a dedicated fellowship, comprising:

  • Monthly stipend of €1,650
  • Monthly research-cost allowance of €100 (Forschungskostenpauschale)
  • Health-insurance subsidy of €100 per month
  • Supplementary €550 mini-job allowance to support parallel part-time employment (optional)

Requirements

Do you have experience in Research?, Do you have a Master's degree?, This PhD position is part of an initiative to advance knowledge representation and adaptive reasoning systems. The research will focus on developing flexible frameworks for actionable knowledge representation that support storage, retrieval, and dynamic adaptation of information across diverse tasks., * Holding recognized MSc degree (or equivalent) in Computer Science, AI, ML, or a related discipline.

  • Students holding BSc degree and exhibiting outstanding performance and extraordinary potential can apply for fast-track PhD.
  • Strong mathematical background supported with experience in defining and developing knowledge-graph or information retrieval systems.
  • Hands-on experience with large language models (LLMs) and their applications.
  • A track record of publications in AI/ML or related areas.
  • Documented experience in practical research work.
  • Strong skills in academic English writing (peer-reviewed papers, reports, or equivalent).

Apply for this position