Germany – PhD in Discovery at Constructor University

Overview

University: Constructor University

Country: Germany

Deadline: Rolling

Fields: Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Systems

Constructor University, formerly known as Jacobs University Bremen, is a leading private, English-language research university located in Bremen, Germany. It fosters innovation and collaboration across scientific disciplines with strong industry partnerships.

The advertised PhD position centers on “Knowledge Discovery:
From Unstructured Data to Shared Cognitive Maps.” The research focuses on knowledge representation and adaptive reasoning to transform unstructured information into interpretable, persistent, and navigable knowledge structures. The project aims to create flexible, actionable knowledge graphs and personalized cognitive maps that support storage, retrieval, and dynamic adaptation across diverse tasks, with applications for transparent, adaptive, and spatially intuitive knowledge systems.

The PhD position is part of a collaborative initiative involving Constructor University, Constructor Knowledge Labs (CKL), and Constructor Technology (industry partner). The research group is led by Prof. Dr. Andrey Ustyuzhanin, an expert in AI and machine learning. Key objectives include:

• Transforming unstructured data into interactive knowledge graphs and personalized cognitive maps.
• Designing interpretable, persistent, and navigable knowledge structures.
• 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 and profile extraction from artifacts like academic papers and courses.
• Enabling cross-domain abstraction to support knowledge transfer and collaboration.

The overarching goal is to develop transparent, adaptive, and spatially intuitive knowledge representation systems for both individual users and collaborative environments.

This PhD position is suited for candidates motivated to tackle complex challenges in AI and knowledge representation. Suitable applicants will possess:

• A recognized MSc degree (or equivalent) in Computer Science, Artificial Intelligence, Machine Learning, or closely related discipline.
• Exceptionally talented BSc graduates with outstanding performance may apply for a fast-track PhD.
• A strong mathematical background, with experience in defining and developing knowledge-graph or information retrieval systems.
• Practical 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 academic English writing skills, demonstrated through peer-reviewed papers, reports, or equivalent.

The ideal candidate will be intellectually curious, proactive, and eager to contribute to the advancement of knowledge representation and adaptive reasoning systems.

Funding for This Position Includes a Comprehensive Fellowship Package

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

Expected start date:
February 2026

• Curriculum Vitae (CV)
• Academic transcripts
• A detailed letter of motivation outlining research interests and career goals
• 2 recommendation letters

Applications will be reviewed on a rolling basis. Shortlisted candidates will be invited to interviews. For further details and to apply, please visit the official job posting: (Use the "Apply for this Job" box below)./

If you are eager to shape the future of knowledge representation and AI, and wish to be part of a world-class research environment in Germany, this PhD opportunity offers a pathway to academic and professional growth. We encourage qualified candidates to apply and explore similar opportunities to advance their careers in the field.