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Research in the Age of AI - Analysing data with AI
Provider: Faculty of Health and Medical Sciences
Activity no.: 3993-26-00-05
There are 52 available seats
Enrollment deadline: 26/11/2026
Date and time
03.12.2026, at: 14:30 - 15:45
Regular seats
96
Contact person
Mia Dabelsteen E-mail address: mia.dabelsteen@adm.ku.dk
Enrolment Handling/Course Organiser
PhD administration SUND E-mail address: phdkursus@sund.ku.dk
Enrolment guidelines
This session is open for PhD students and postdocs with an interest in the topic at the Faculty of Health and Medical Sciences
Content
Generative AI can support tasks such as data cleaning, coding, statistical analysis and code generation. But how do you assess whether an AI-supported analysis is actually sound?
In this interactive workshop, we will explore opportunities and limitations of using AI in data analysis, with a focus on verification, reproducibility and avoiding black-box approaches. We will also discuss how to maintain scientific judgement and communicate AI-supported analyses transparently.
The session combines a short expert input with reflection and discussion based on research practice.
No prior experience with generative AI is required. Please bring a laptop or other device, as you may be invited to try out selected AI-supported approaches during the session.
Facilitated by Nicole Schmitt and TBA, HEADS.
About the speaker
• Nicole Schmitt is professor in Blended Learning at the Dept. of Biomedical Sciences at SUND. She is elected chairperson of the PhD Study Board at SUND and leader of SUND’s Centre for Online and Blended Learning.
Time and date
: Thursday 3 December 2026, 14:30-15:45.
Registration
: Please register no later than 26 November 2026.
Venue
: Panum, Blegdamsvej 3B, Maersk Tower, 1.st floor, Holst Auditorium.
Organizer
:
Mia Dabelsteen, mia.dabelsteen@adm.ku.dk, senior consultant, The Graduate School.
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Research in the Age of AI is a series of interactive 75 min-sessions for PhD students and postdocs at HEALTH exploring how generative AI is changing research practice. Each session focuses on a specific aspect of research and combines a short expert input with reflection, discussion and exchange across disciplines. The aim is to support informed and responsible use of AI while keeping scientific judgement, research integrity and researcher responsibility central. Sessions can be attended individually.
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