The PhD topics will be in the context of the Open Research Knowledge Graph (https://www.orkg.org) and the project “SCINEXT - Neural-Symbolic Scholarly Innovation Extraction”, funded by the Federal Ministry of Education and Research (BMBF). The aim of these projects is to research and develop techniques for crowdsourcing, representing and managing semantically structured, rich representations of scholarly contributions and research data in knowledge graphs and thus develop a novel model for scholarly communication. In the context of the PhD thesis you will be responsible for building and maintaining the ORKG data ingestion and processing pipelines to ensure the flow of high-quality semantified resources from publications. Your main responsibility in this position will be to build scalable solutions that crawl, ingest, process publications, and thereby enrich the ORKG. You will work alongside the ORKG engineering team to set up the AI/NLP ecosphere.
Your tasks will focus on