Master Thesis - Knowledge Capture

Your tasks

In this Master's thesis, a Python package will be developed to create accessible knowledge that comprises a first goal towards our vision. Public employee data of the research unit, such as names, titles, roles, and affiliations, will be collected. In addition, all open-access publications from the last ten years will be downloaded. With the help of Large Language Models (LLMs), these data will be structured, and a knowledge graph will be developed. The knowledge will then be stored in a Graph Database, and examples of potentially relevant queries for strategic decisions are provided.

The tasks include:

• Collect publicy available data
• Develop a Python package that
• brings the data in a structured format like JSON, LLMs can be used
• extracts a knowledge graph from the structured data, human interaction might be required
• generates CYPHER queries to upload these data into a Graph Database

• Generate and provide relevant example queries to demonstrate the usefulness of the approach

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
• 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]