Disease Modeling Research Grant: up to USD 5,000 in research support
2026-08-21
Researchers interested in the practical and responsible use of artificial intelligence in data analysis are invited to join the Nature Masterclasses webinar “Community Insights: Analysing and Interpreting Your Research Data with AI.”
Artificial intelligence can support many stages of research, from data collection and preparation to coding, modelling, pattern recognition, troubleshooting, interpretation and visualisation. The webinar will focus on how to make effective use of these tools while maintaining robust research methods and appropriate human oversight.
What will the webinar cover?
Participants will learn how to:
- use AI at different stages of data analysis, from planning and preparation to interpreting scientific results,
- critically assess AI-generated outputs and recognise situations where expert judgement remains essential,
- protect sensitive and unpublished research data,
- identify and manage risks related to bias, privacy and data security,
- document the use of AI and follow institutional, funder and publisher guidelines,
- use AI to support, rather than replace, analytical thinking and research expertise.
The webinar will feature experts in AI research, scientific publishing, research integrity and data analysis. Participants can also submit their own questions during registration.
EMEA session
Date: Thursday, 17 September 2026
Time: 14:00-15:00 BST (15:00-16:00 CEST)
The EMEA panel will include Ellie Gendle, Head of Journals Policy – Research Integrity at Springer Nature; Oliver Graydon, Chief Editor of Nature Photonics; Samraat Pawar, Professor of Theoretical Ecology at Imperial College London; and Nicki Tiffin, Professor at the University of the Western Cape and Deputy Director of the South African National Bioinformatics Institute.
More information and registration details are available in the attachment: https://mlodanauka.umw.edu.pl/wp-content/uploads/2026/08/NMO-AI-Webinar-Analysing-and-Interpreting-Your-Research-1.docx
