Postdoctoral Researcher in NLP for Historical Texts
1 month ago
As a Postdoctoral Researcher in Natural Language Processing (NLP) at Københavns Universitet, you will contribute to advancing our understanding of diachronic language development in historical documents. The successful candidate will join an interdisciplinary research team and apply computational methods to effectively retrieve, process, analyze, and interpret relevant historical texts.
The position is a full-time, fixed-term appointment for 2 years, starting from 1 January 2025. We offer a competitive salary and benefits package, including a total pension contribution of 17.1%.
Key Responsibilities- Develop and implement NLP methodologies for processing multilingual historical texts.
- Collaborate with historians, computational linguists, and digital humanities researchers to ensure successful integration of NLP techniques into historical research.
- Publish research findings in peer-reviewed journals and present at international conferences.
- A Ph.D. in Computer Science, Computational Linguistics, or a related field with a focus on NLP.
- Demonstrated expertise in key NLP methodologies, including text preprocessing, OCR post-correction, named entity recognition, part-of-speech tagging, syntactic and semantic parsing, machine learning approaches, deep learning techniques, information retrieval and extraction, sentiment analysis, topic modeling, and interpretable NLP.
- Familiarity with historical textual data and willingness to tackle challenges specific to this domain, such as handling archaic language, dealing with OCR errors, contextualizing historical events, and ethically handling racialized and gendered language.
- Proficiency in Python and other relevant programming languages, along with experience with NLP libraries and frameworks like NLTK, spaCy, TensorFlow, PyTorch, or similar.
We are seeking a highly qualified candidate with a strong background in NLP and a keen interest in applying their expertise to collaborative historical research on Atlantic colonial history. A strong publication record in NLP and computational linguistics conferences and journals is essential. Familiarity with historical research methodologies and sources, as well as experience with collaborative, interdisciplinary research environments, is also desirable.
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