Post-doctoral Research Associate in Computational Linguistics
Core
Co-leading the computational stream of a 5-year ERC-funded project to develop algorithms for time-sensitive word sense disambiguation in Latin and conduct large-scale quantitative analyses of semantic change.
Role type
Post-doctoral Research Associate in Computational Linguistics
Builds
Novel algorithms for time-sensitive word sense disambiguation (WSD) in Latin, a 100-million-token annotated corpus, and open-source tools for historical semantics.
Domain
Computational Linguistics, Historical Linguistics, Digital Humanities, Latin
Deliverable
production ML models | research
Required skills
Computational semantics models, word sense disambiguation, semantic change detection, Python, NLP libraries, large-scale corpora, annotation pipelines
Preferred skills
Historical texts, historical languages (Latin), corpus annotation standards, diachronic NLP, time-sensitive semantic modelling
Technologies
Python, NLP libraries
Responsibilities
Develop novel algorithms for time-sensitive word sense disambiguation in Latin, contribute to the creation of a 100-million-token annotated corpus, conduct large-scale quantitative analyses of semantic change, integrate linguistic insights into computational models, build open-source tools and resources.
Seniority
Post-doctoral, hands-on IC
