How can generative AI support your everyday research practice in the natural sciences without replacing critical judgement, subject expertise or scientific responsibility? This online workshop series is designed for PhD Candidates and Postdocs who want to develop a sound understanding of how generative AI works, where its limitations and risks lie, and how legal, organizational and academic guidelines shape its use in research contexts.

The first session focuses on basic principles, data protection, confidential research data, academic integrity, transparency, documentation and structured prompting with KI-Chat@JGU. Between the two sessions, participants will test AI applications in their own research or work context. The second session builds on these experiences and focuses on prompt refinement, quality assurance, context engineering and the development of responsible AI-supported workflows.

The central question throughout is how AI can support scientific work in a useful and accountable way while keeping scholarly responsibility and expert assessment with the researcher.

Language-proficiency level minimum English C1 (CEFR).

PhD Candidates and Postdocs of the Natural and Life Sciences, Mathematics, and Psychology.