Akademische/-r Mitarbeiter/-in (w/m/d) im Bereich Wissens- und Technologietransfer - 369/2026
Core
Research and development of agent-based simulations and policy evaluation using AI methods (LLMs, text mining) to study systemic transfer barriers between science, business, and society.
Role type
Research academic staff (postdoc level) in computational social science and agent-based modeling
Builds
Theoretical contributions to transfer research and practical support for master's level seminars on LLMs and AI agents
Domain
Computational Social Science / Economics / AI Policy
Deliverable
production ML models
Required skills
Agent-based modeling, quantitative modeling, simulation methods, programming for complex simulation implementation, LLMs and text mining
Preferred skills
Teaching experience, evaluation of political/economic decision processes
Technologies
LLMs, text mining, agent-based simulation frameworks
Responsibilities
Conduct research on autonomous generative AI agents, support master's seminars on LLMs and AI agents, bridge theoretical simulation models with applied policy analysis, contribute to research-oriented master's education
Seniority
Junior Researcher / Postdoc
