LAVA is a transfer project with the aim of making knowledge graph related research results available as accessible, reusable software components and test and evaluate them in a medical context. The focus will be on problems like relation extracion and fact validation, entity resolution, knowledge graph validation and maintenance, and others.
For the project, we are looking for a PostDoc researcher with a background in knowledge graph technology (experience with one or more techniques such knowledge graph embedding, relation extraction, knowledge graph matching, etc. is a strong plus) and a passion for creating reusable software artifacts.
What we offer: working in a great, international, and diverse team of researchers in knowledge graphs, machine learning, NLP, and more. Rich opportunities for pursuing own research ideas. Nice campus in the city center of one of the sunniest cities in Germany.
The position is open until filled, with a starting date in summer or autumn 2024. Salary is E13 of the public payscale (52k to 65k per year, depending on prior work experience).
If you are interested, please send your application (CV, link to Google scholar profile) to Heiko Paulheim.