Opening internship master student(s) MBCS – 2026

Department: Human Aligned Video AI (HAVA) lab & Institute of Informatics (IVI)

Supervision: Anne Zonneveld (a.w.zonneveld@uva.nl), dr. Iris Groen (i.i.a.groen@uva.nl)

Summary:

Human visual perception occurs in a dynamic world. Although static images are frequently used in visual perception studies, they do not encompass the full range of possible events and lack temporal context, which affects cognitive processing and its neural dynamics (Willems & Peelen, 2021). Therefore in the current project we will focus on the neural processing of natural videos vs static images using EEG-recordings. Data from seven participants are already available for analysis, allowing the student to start immediately, and additional data will be collected in parallel.

Duties:

– Assist in EEG data collection
– Analyse EEG data using computational frameworks like representational similarity analysis (RSA) (Kriegeskorte et al, 2008)
– Explore analyses using image and video based deep neural networks (DNNs)

Requirements:

– Basic skills in programming (Python)
– Familiarity with EEG-recordings is preferred
– Familiarity with usage of DNNs is preferred
– Interest in visual perception

Benefits:

– Gain hands-on experience in EEG recording and analysis
– Mentorship in neuroscience and computational techniques
– Potential opportunities to contribute to publications

Dates: February 2026 – June 2026 (exact dates can be discussed – earlier starting date for the option of a bigger research project is also possible)

Location: Amsterdam. As we will be collecting EEG data, in-person availability is required.

How to apply:  send your CV, small motivation and academic transcript to a.w.zonneveld@uva.nl.

References

Willems, R. M., & Peelen, M. V. (2021). How context changes the neural basis of perception and language. IScience, 24(5)

Kriegeskorte, N., Mur, M., & Bandettini, P. A. (2008). Representational similarity analysis-connecting the branches of systems neuroscience. Frontiers in systems neuroscience, 2, 249.