Workshop series: "Using AI in Your Doctoral Research"
How can AI be used effectively in doctoral research and everyday academic work – and where are the limits and grey areas? In this workshop series with Dr. Johanna Scheel, participants will have the opportunity to explore different AI applications hands-on and apply them to concrete tasks from their own research and academic work – from structuring and analysing data to working with texts and organising their work.
The workshops will also address data protection, legal and institutional requirements, as well as research integrity and good scientific practice, including how to document and appropriately cite the use of AI. Participants are encouraged to bring their own experiences, questions, and examples, creating space for discussion, reflection, and shared learning. The aim is to build confidence in using AI as a responsible and effective tool while safeguarding academic integrity, individual scholarly contribution, and responsibility.
The in-depth modules in November and December can be booked individually; however, participation in the Kick-Off Workshop in October is a prerequisite.
Powered by Promotionskolleg Brandenburg / Brandenburg Graduate School for Applied Sciences.
16/10/2026, 9.00 am – 1.00 pm
Fundamentals and Frameworks of AI in Doctoral Research (Kick-off)
How can AI use be documented transparently, systematically, and in a way that also adds value to your own work? This Deep Dive explores relevant requirements, grey areas, and practical documentation strategies and applies them to participants’ own academic work. Participants will also create a personal prompt and context library to systematically collect, organise, and reuse effective prompts for their future work.
02/11/2026, 9.00 am – 11.00 am
Documentation of AI Use – Evidence and Personal Benefit (Deep Dive 1)
How can the use of AI be documented in a transparent and systematic manner, whilst also adding value to one’s own work? In this deep dive, relevant requirements, grey areas and practical documentation strategies will be examined and applied to the participants’ own academic work. Participants will also create a personal library of prompts and contexts to systematically collect, organise and reuse effective prompts for their future work.
06/11/2026, 9.00 am – 11.00 am
AI and GSP, research integrity, deskilling (Deep Dive 2)
How can AI be used without losing sight of individual contribution, research integrity, and essential academic skills? This Deep Dive explores different forms of AI use and addresses questions of authorship, transparency, and academic responsibility, as well as cognitive offloading, de-skilling, and the conscious use of AI as a support for thinking and working. Using concrete scenarios from doctoral research and academic work, participants will develop personal principles for a self-directed and skill-enhancing approach to AI.
27/11/2026, 9.00 am – 11.00 am
Context Engineering / context management (Deep Dive 3)
Why can the same prompt produce very different results depending on the context – and how can context be used strategically to improve the quality of AI outputs? In this Deep Dive, participants will learn how to select relevant information and materials, prepare them in an AI-readable format, and experience the difference firsthand using their own examples. Step by step, they will build a personal context library with reusable building blocks for their own research and academic work, alongside the prompt library introduced in Deep Dive 1.
04/12/2026, 9.00 am – 11.00 am
Building Your Own AI Assistants/Tutors (Deep Dive 4)
Where could specialised AI assistants meaningfully support your own doctoral research and academic work? In this Deep Dive, participants will use a prompt template to develop their own AI assistant or AI tutor, test it with the AI tools available to them, and reflect on its possibilities, limitations, and the responsibilities involved. A brief introduction to AI assistance and agentic AI will also provide an outlook on future possibilities for shaping and enhancing their own academic workflows.
