Thesis Supervision

Due to the high demand and, at the same time, close integration of students into our research programme, the number of thesis students in the lab is limited. To deal with the large number of applications, we have implemented the following procedure. It is in place for efficiency reasons, and to make sure that we can offer the best supervision possible for projects that are an ideal fit to the candidate’s background and skillset.

The lab operates largely in two domains, one more related to advanced analyses of brain data (ephys, fMRI, etc.), the other being more related to computational modelling, which includes the development, training and analysis of deep neural networks in various shapes and forms. While we ultimately look at both together, the day-to-day for the thesis student is quite different. Please indicate in your application which overall direction you are more interested in.

The skillset that we are looking for, to avoid frustration on both sides, is:

• Very good coding skills (python)
• Knowledge of machine learning/data science
• Basic knowledge of (visual) neuroscience and linear algebra
• Ideally: successful participation in the ML4CCN, or other coursework offered by the lab

Please follow this procedure to apply for thesis work in the Kietzmann lab

1. Please contact Anastasia Derksen to express your interest. In the email, send a short motivation text and your transcript (or a list of relevant coursework). The transcript is needed for us to understand whether your skillset/educational background fits the projects available in the lab.
2. Once a semester (next deadline: 17th of Febuary), the team meets to discuss the applications. Eligible students will be notified via email.
3. On March 10, from 2-4pm, all candidates meet with the Team for a joint “Thesis Fair” afternoon. Here, we present all available topics in depth, and students can express their interest to working towards each one
4. Once a match is found, we begin the onboarding process.
5. Students then regularly meet their supervisor, take part in lab meetings, etc. and become a member of the research team.