This seminar provides a practical and research‑oriented introduction to how AI tools can be used effectively in academic work. Through three complementary presentations, the seminar explores general use of AI tools, coding and data analysis with AI support, and the use of AI as an assistant in research funding applications. Together, the presentations offer a broad overview of how AI can be integrated into everyday academic workflows. The presenters are not AI specialists by training. Instead, they are researchers from different disciplines who have learned to use AI tools through hands‑on, bottom‑up experience in their own work. The seminar is therefore grounded in practical use cases and real research contexts, rather than technical or theoretical expertise in artificial intelligence.

Nicolò is an archaeologist specialising in digital technologies, 3D visualisation and data analysis. In his presentation, he provides an overview of different AI platforms and their strengths for various types of tasks. He demonstrates how project‑based workspaces can be set up and customised within AI tools, such as ChatGPT, to support more effective, consistent, and purposeful work. The focus is on practical aspects of organising and interacting with AI tools, including how clear instructions and well‑structured inputs can improve results.

Karin is a bioinformatician working with bioinformatics and omics data. Her presentation addresses how AI tools can be used to support coding and data analysis in research contexts. She discusses different tools for code generation, debugging, and documentation, and how these can be integrated into existing workflows. Particular attention is given to limitations, risks, and what to be aware of from a quality and reproducibility perspective.

Anna is a statistician and epidemiologist who primarily works with register‑based studies. In her presentation, she focuses on the use of AI as a practical assistant in the research funding application process. She provides examples of how AI can support the identification and comparison of funding bodies, help structure and summarise texts, and simulate peer‑review feedback. The emphasis is on using AI to increase efficiency while maintaining responsibility for the scientific content and overall quality of the application.

Overall, the seminar focuses on concrete workflows, methodological considerations, and responsible use of AI in academic research settings. It is aimed at researchers and research‑support staff who want to better understand how AI can be used as a practical tool in their work, without compromising scientific integrity, quality, or accountability.

REGISTRATION
The seminar is free of charge but if you wish to have a lunch sandwich you need to register before the 21th of May:
https://survey.mailing.lu.se/survey/65255