Mandatory Internship / Thesis: Visual & Natural Language Interaction for Knowledge Graph Retrieval (Waldkirch (near Freiburg), Waldkirch (near Freiburg), Waldkirch (near Freiburg), Waldkirch )
At a glance
Junior AI Research role at SICK. Waldkirch (near Freiburg), Waldkirch (near Freiburg), Waldkirch (near Freiburg), Waldkirch.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Improve retrieval by combining embeddings and knowledge graphs with symbolic or query-based techniques
- Test retrieval quality, explainability and user interaction patterns
- Design a visual or graph interface that works alongside natural-language interaction
- Build and validate a prototype feature to show the proposed ideas
What you bring
- You are studying computer science, data science, information systems, AI, HCI or a related subject
- You have a solid technical foundation and an interest in intelligent information systems
- You are comfortable prototyping and experimenting, and interested in working across disciplines
Who this fits
This fixed-term internship or thesis suits a bachelor’s or master’s student who wants to shape the project focus around their background and interests. The placement is for three to six months during the summer semester of 2027.
From the employer
Summer Semester 2027 – fixed term of 3–6 months
We are developing new ways to work with enterprise knowledge by connecting information across domains and systems using semantic technologies, knowledge graphs and AI-powered services. An initial MVP has been implemented, combining graph-based hybrid retrieval with a natural language interface. Inspired by cognitive science, the concept aims to make complex information systems more intuitive and easier to use. For the next iteration, we are looking for an intern or bachelor’s or master’s student to help develop and evaluate the concept further. You will contribute directly to an innovation project and have the opportunity to shape the focus of your internship or thesis around your background and interests.
YOUR TASKS:
Depending on your interests and the scope of your internship or thesis, you may focus on one or more of the following areas:
- Improve hybrid retrieval methods by combining embeddings, knowledge graphs and symbolic or query-based approaches.
- Explore and evaluate retrieval quality, explainability and user interaction patterns.
- Develop concepts for a visual or graph-based interface that complements natural language interaction.
- Implement and validate a prototype feature to demonstrate the proposed concepts.
YOUR PROFILE:
- Degree studies in computer science, data science, information systems, artificial intelligence, human-computer interaction or a related field
- Solid technical background and an interest in intelligent information systems
- Curiosity about user experience, cognitive science, knowledge representation or human-centered AI
- Confidence in prototyping and experimentation, with an interest in interdisciplinary collaboration
Contact: Sarah Disch
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