TU Dresden
A joint project with Uni Leipzig DE EN

Intuitive Modelling support for Knowledge-Based Systems

Mentored by Carsten Lutz, Sebastian Rudolph, Markus Krötzsch
at Leipzig University or TU Dresden

Many symbolic AI applications rely on the presence of well-formalized ontologies that capture the application domain’s background knowledge in order to make better use of available data by means of logical inferences. In practical application scenarios, domain experts cannot be expected to be trained in logical modelling, which leads to the notorious knowledge acquisition bottleneck.

We aim to address this dilemma by developing innovative approaches and methodologies that enable domain experts to produce well-modelled ontologies in an intuitive and efficient manner. These methodologies will involve techniques from data mining and machine learning and have both interactive and fully automatic aspects.

Work Environment

You will be working in an international team with a strong reputation in the areas of ontology and knowledge graphs, embedded in a collaborative ecosystem of several groups working in the area of computational logic.

If required, you will have access to the HPC resources of the ScaDS.AI Center for Scalable Data Analytics and AI Dresden/Leipzig, offering state-of-the-art CPU and GPU resources, as well as high-performance computing and storage systems for computational experiments.

Prerequisites

  • Master’s Degree (or equivalent) in computer science, mathematics, or a closely related field.
  • Solid background in formal logic and good programming skills.
  • Ability and willingness to collaborate in an interdisciplinary environment.
  • Practical experience in the technical evaluation of software systems and execution of user studies are beneficial.