A postdoctoral position is available at TU Wien, Austria. The duration of the position is up to 6 years. The position is available immediately with a flexible starting date within the next couple of months.

The research will be concerned with using knowledge graphs and graph technologies to enable novel perspectives of analysis and make data and results accessible through the integration of heterogeneous data, such as environmental data, genomes, ontologies, publications, external data. Of particular interest are the scalable support of evolving data, provenance, exploration, analytics, graph embeddings, and knowledge sharing.


  1. Large-scale integration of heterogeneous data using graph technologies

  2. Graph data evolution, provenance, and explainability

  3. Data mining and machine learning on graphs

  4. Exploratory analytics over graph data


  1. PhD in computer science or data science

  2. Excellent scientific background and publication record

  3. Demonstrated ability to work independently as well as in a team

  4. Excellent communication skills in English, oral as well as written

  5. Good programming skills

Advanced experiences in at least 2 of the following areas:

  1. Graph data management and querying

  2. Data integration (data lakes, fabrics), data quality, provenance

  3. Machine Learning, explainable AI, federated learning

  4. Semantic Web Technologies, Linked Data

  5. Dynamic knowledge graphs

  6. Exploratory analytics


  1. Perform excellent scientific research

  2. Develop research prototypes and conduct experiments

  3. Publish in international conferences and journals

  4. Participate in activities of the group and the department

  5. Participate in research projects funded by internal and external sources

The indication of interest should contain:

  1. Cover letter (max. 1 page), including (i) motivation for applying, (ii) preferred starting date, and (iii) a brief explanation of the applicant’s background.

  2. Research statement (project description) roughly within the frame of one of the topics mentioned above (max. 2 pages excl. references). This description should outline the applicant’s thoughts and ideas on possible research directions within the context of the preferred topic. 

  3. CV

  4. Copies of certificates and grade sheets for all obtained degrees (English)

  5. Recommendation letters or contact information of at least two references


The material should be sent as a single PDF to Katja Hose (katja.hose@tuwien.ac.at).

Postdoctoral Fellowship in Knowledge Engineering and Graph Data Management