Master Thesis - RAG-Powered LLM Chatbot

Your tasks

In this Master's thesis, a ChatBot Python package will be developed. Large language models (LLMs) will be used and grounded with a knowledge graph of information on the researchers of our research unit, their roles, and their research, technologies, and devices. Retrieval augmented generation (RAG) will mitigate knowledge gaps, factuality issues, and hallucinations of (ungrounded) LLMs with external/domain-specific knowledge. The ChatBot will serve as a user-friendly, human-like interface for non-computer scientists involved in strategic processes, making it easier for them to access and understand these data.

The tasks include:

• Develop a ChatBot Python package (utilizing an in-house existing prototype) that is based on Large Language models
• Develop a retrieval augmented generation solution to ground this LLM with knowledge stored in a Graph Database
• Sophisically engineer prompts to allow correct responses to the project relevant questions
• Provide visuals for show cases

We offer

• Excellent supervision that supports your personal and professional development
• Exciting insights into the work of a leading research institute
• The chance to work in interdisciplinary, international teams and benefit from a wide range of perspectives
• The opportunity to contribute and actively shape your own ideas and impulses
  right from the start
• Modern technical equipment and IT service to optimally support your work

Your profile

• Background in Computer Science
• Advanced understanding of large language model (LLMs) APIs
• Solid programming skills in Python
• Experience with software development in an IDE (JetBrains PyCharm)
• Experience with collaborative software development and agile project management with Git
• Database experience and database querying languages, preferably with graph databases and CYPHER
• Fluent in spoken and written English

Diversity and Inclusion

The UFZ has a strong commitment to diversity and actively supports equal opportunities for all employees regardless of their origin, religion, ideology, disability, age or sexual identity.
We look forward to applications from people who are open-minded and enjoy working in diverse teams.

Important

Please submit your application via our online portal with your cover letter, CV (please omit your photo, age, or marital status) and relevant attachments.

Contact

Your contact for any questions you may have about the job:
Prof. Dr. Jana Schor
Bio-Data Science Group
[email protected]