Artificial Intelligence in Your Early Career Research Workflow

Using AI responsibly and effectively in everyday research work – with a spotlight on scientific writing

Artificial intelligence (AI) is becoming part of everyday academic practice – whether you already use AI regularly or are just starting to explore its potential. For doctoral candidates and other early career researchers (ECRs), the key challenge is not whether to use AI, but how: in a way that is meaningful, responsible and aligned with institutional and legal requirements.

This two-part workshop series supports doctoral candidates and other ECRs in developing a confident and structured approach to AI use in their doctoral research. The focus lies on practical application using the university’s own AI infrastructure (KI-Chat@JGU) and on integrating AI into typical ECR workflows in a sustainable way.

What you will gain:
After completing the workshop series, participants will be able to:

• understand how generative AI works and where its strengths and limitations lie in a research context,
• use KI-Chat@JGU confidently for typical researcher-related tasks such as literature research, text work, structuring arguments or data-related tasks,
• assess what is permissible and responsible when using AI in their own research, based on relevant legal and institutional frameworks,
• develop effective prompting strategies tailored to their own research needs,
• reflect on their own AI use and build routines for integrating AI into everyday doctoral work in a structured and time-efficient way.

Course structure:

The workshop series consists of three half-day online sessions with a practice phase in between.

Part 1: Getting started with AI in the research context (Johanna Scheel)
Participants build a shared understanding of generative AI and explore how AI can support typical tasks in the research process. Using KI-Chat@JGU, they work hands-on with concrete examples from their own research practice and learn how to formulate prompts that are useful and reliable.

Part 2: Scientific Writing (Amanda Habbershaw)
This hands-on workshop explores both the possibilities and limitations of using AI in scientific writing. Participants will evaluate and improve their own texts while critically reflecting on AI-generated suggestions. With practical guidance from the trainer, using KI-Chat@JGU, you will refine a short text prepared in advance of the workshop. Drawing on these experiences, the group will jointly develop a set of current best practices for writing with AI.

Practice phase:
Between the workshops two and three, participants apply what they have learned in their everyday research work and collect questions, challenges and experiences.

Part 3: Reflection and further development (Johanna Scheel)
The third workshop focuses on reflecting on these experiences, discussing good practices and refining individual AI workflows. Depending on the group’s interests, selected advanced use cases may be addressed. The workshop concludes with concrete next steps for continued and responsible AI use during the  doctorate.

Teaching approach:
The workshops are interactive and practice-oriented. Short input phases alternate with hands-on exercises, individual reflection and peer exchange. Participants work with their own research-related examples, ensuring direct relevance and transfer to their doctoral work.

Target audience: All TransMed fellows

Maximum number of participants: 15

Technology: Zoom
Please check that your PC meets the requirements beforehand (microphone, camera, Internet connection).  

Next workshop: 
Part 1: April 23, 9.00 am - 1.00 pm
Part 2: April 29 or 30; 9.00 am - 12.00 pm each, two small working groups by arrangement 
Part 3: May 27, 9.00 am - 1.00 pm

TransMed Credit Points:  1.4 CP for transferable skills training