Akademische/-r Mitarbeiter/-in (w/m/d) im Bereich Wissens- und Technologietransfer - 370/2026
Core
Research and design the interface between science, business, and society using AI-driven methods like text mining and LLMs to investigate systemic transfer barriers.
Role type
Academic researcher (PhD-track) in AI-driven text mining and innovation management
Builds
Theoretical contributions to transfer research and practical teaching modules on quantitative text analysis and AI tools
Domain
Higher Education / Computational Social Science / AI & NLP
Deliverable
research
Required skills
Text mining, LLMs, Python programming, handling large unstructured text corpora, quantitative text analysis, validation methods
Preferred skills
Teaching experience, interdisciplinary collaboration, knowledge of German innovation system
Technologies
Python, LLMs, Text Mining tools
Responsibilities
Support computer-assisted quantitative method training at Bachelor level, co-teach seminars on text mining and LLMs, develop AI-driven text mining procedures, conduct research on validation and error calculation in LLM-based analysis
Seniority
Junior/Mid-level Academic Staff (Academic Employee)