Constructor University, in collaboration with Constructor Knowledge Labs (CKL) and Constructor Technology, is inviting applications for a PhD Researcher position in Computer Science. This scholarship focuses on Artificial Intelligence (AI) and Machine Learning (ML), specifically in advancing knowledge representation and adaptive reasoning systems. This is an excellent opportunity for aspiring researchers to contribute to cutting-edge developments in AI and knowledge discovery.
PhD Researcher Scholarship: Knowledge Discovery from Unstructured Data to Shared Cognitive Maps at Constructor University
Designation
- PhD Researcher
Funding & Appointment Terms
The appointment provides full financial coverage through a dedicated fellowship:
| Benefit | Amount (Monthly) |
|---|---|
| Monthly Stipend | €1,650 |
| Monthly Research-Cost Allowance (Forschungskostenpauschale) | €100 |
| Health-Insurance Subsidy | €100 |
| Supplementary Mini-Job Allowance (optional) | €550 |
Research Area
- Computer Science, with a focus on Artificial Intelligence (AI) and Machine Learning (ML).
- Key research objectives include:
- 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.
Location
- Bremen, Germany
Eligibility/Qualification
- Holding a recognized MSc degree (or equivalent) in Computer Science, AI, ML, or a related discipline.
- Students holding a BSc degree and exhibiting outstanding performance and extraordinary potential can apply for a 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).
Scholarship Description
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. The overarching goal is to create systems that enable transparent, adaptive, and spatially intuitive representations of knowledge, supporting both individual users and collaborative communities.
How to Apply
The application package must include:
- Curriculum Vitae (CV)
- Academic Transcripts
- A detailed letter of motivation outlining research interests and career goals
- 2 recommendation letters
- Bachelor and Master’s diploma (in original language and English)
Applications will be reviewed on a rolling basis. Shortlisted candidates will be invited to interviews.
Last Date for Apply
Applications are reviewed on a rolling basis, so early application is encouraged.
Apply Link
