Job Vacancy: Machine Learning for Information Extraction from Ancient Texts on the NIKAW Project

Within the context of the ID-N project NIKAW (Networks of Ideas and Knowledge in the Ancient World), funded by the Special Research Fund (BOF) of KU Leuven, applications are invited for a PhD position on the subject of machine learning for information extraction from ancient texts. The NIKAW project aims to exploit textual information from the ancient world to reconstruct the transmission of knowledge across multilingual, geographically and chronologically extended communities. 

The PhD candidate will focus on the extraction of relevant information from Ancient Greek and Latin texts, which will subsequently be used for further analyses within the project. Part of the tasks will be carried out in collaboration with another PhD student and one Postdoc. Research will be carried out along three tracks:

  • Firstly, the candidate will develop a state of the art natural language processing pipeline for named entity extraction and named entity linking, specifically tailored towards classical texts. 
  • Secondly, the candidate will develop a bilingual language model (Ancient Greek-Latin), based on neural NLP methods, that will facilitate named entity extraction and linking, and the representation of the context of the mentions in the corpus used.
  • Thirdly, the candidate will improve the natural language processing pipeline by making use of additional information developed by other project members. This includes knowledge on potential linguistic and personal relations gained from social network analysis and learned network embeddings.

The deadline to submit an application for this PhD position is 8 September 2022. The candidate is expected to start in November 2022 or as soon as possible thereafter. The position is a full-time position for one year and can be extended to four years pending initial positive evaluation. 

For more information on the desired profile and how to apply, see the full job listing on the KU Leuven job portal. 


Print Friendly, PDF & Email