AI: PAGE Lab: Two PhD Positions on Interdisciplinary Research in NLP, Knowledge Graphs and History

Your work tasks

AI: PAGE Lab is seeking two highly motivated PhD researchers to join our interdisciplinary team working at the intersection of NLP, KGs, and digital cultural heritage. The two PhD candidates will collaborate closely to develop an ontology-guided pipeline for constructing Knowledge Graphs from historical texts and investigate how such structured representations can support new forms of historical inquiry.

Stipend 1:

The PhD student, hosted by the Department of Computer Science, will focus on developing scalable AI and NLP methods for Knowledge Graph Construction.

Stipend 2:

The PhD student, hosted by the Department of Society and Politics, will guide the Knowledge Graph Construction using their domain knowledge and apply the resulting Knowledge Graphs to conduct graph-based historical analysis, particularly prosopography and social history. The data for the project stems mainly from the nineteenth century, particularly texts from police gazettes and newspapers.

Possible research topics for both stipends can be (but are not limited to):

• Ontology-Guided Knowledge Graph Construction: Developing automated pipelines leveraging LLMs that extract entities, relations, and contextual descriptions from historical texts and integrate them into scalable, interoperable KGs.
• NLP for Historical Texts: Designing and adapting NLP techniques to handle the linguistic variability, ambiguity, and noise typical of historical sources.
• Graph-Based Prosopography and Social History: Developing computational approaches for analysing life-courses, networks and relationships between historical actors using Knowledge Graphs.
• Knowledge Graph Exploration and Analysis Tools: Creating methods and platforms that enable historians and cultural heritage researchers to query, explore, and discover patterns and hidden connections in large historical datasets.

Your competencies

We are looking for candidates motivated to make fundamentally scientific contributions to NLP, KGs, and Digital Cultural Heritage research.

Stipend 1:

Applicants for the position in the Department of Computer Science must have:

• A relevant MSc degree (e.g., Computer Science, Software Engineering, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field)
• Strong programming skills (e.g., Python)
• Strong skills in machine learning, deep learning and modern NLP techniques.
• Background in Knowledge Graphs and LLMs is advantageous but not a requirement.
• Excellent communication skills in English.

Applicants are required to submit, along with their application documents, indicating their vision for research to be conducted in relation to the project topics outlined above – 2-4 pages.

Stipend 2:

Applicants for the position in the Department of Society and Politics must have:

• A relevant MA degree (e.g. History, Archival Studies) or BA degree and completed coursework for the first year if an MA, if applying for the integrated stipend
• Experience with archival research
• Skills in digital history (e.g. dataset creation, information extraction, data visualisation)
• Strong skills in academic writing
• Proficiency in historical Danish

How to apply

Your application must include the following:

Stipend 1:

• Application, stating reasons for applying and qualifications in relation to the position,
• Curriculum Vitae (CV)
• Diplomas (bachelor’s and master's degree diploma, including grades)
• Project description
• Other relevant documents

Stipend 2:

• Application, stating reasons for applying and qualifications in relation to the position,
• Curriculum Vitae (CV)
• Diplomas (bachelor’s and master's degree diploma, including grades)
• Project description of approx. 8 pages.