The candidate will work in high visibility projects as a Data Scientist, bringing the Data Science and NLP expertise to projects. The candidate will work in RD Data Science team and collaborate with Product's managers, domain experts, Knowledge representation experts, to build high value outcome from Elsevier content. The candidate will have an opportunity to impact virtually all Elsevier applications related to Research and Operations.
In this project, we would like ti train embedding models to represent tables in scientific articles. For embedding tables, we would like to experiment with a wide rage of methods including structured models such as TaBERT and StruBERT; multi-vector embeddings; summarization-based encoding (summarize tables and then embed them); hierarchical table embedding.
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