项目介绍

2025年3月24日

The lab of Kobe Desender is at the forefront of research in decision making, decision confidence and cognitive control, using a variety of methods, including carefully controlled behavioral experiments, computational modeling (Reinforcement Learning; Drift Diffusion Modeling), and advanced EEG analysis (multivariate decoding; model-based EEG). Please have a look at the lab philosophy to get a better view of the lab’s functioning (https://desenderlab.com/lab-philosophy/). The team of Hans Op de Beeck focuses upon the neuroscience of vision and learning, for more information see hoplab.be. KU Leuven is one of the best European universities according to international rankings (e.g., #45 world-wide in the Times Higher Education ranking). Both research groups belong to the department of Brain & Cognition, which contains around 100 scientists, many of them with interest in vision, cognition, and neuroscience, and to the Leuven Brain Institute that includes more than 150 research teams in neuroscience. Our labs and office spaces are located in the centre of Leuven. Leuven is a vibrant university town which is only a 25-minute train commute from the centre of Brussels and its international train hub (with 2-hour train rides to Paris, London, and Amsterdam). From Leuven it also only takes a 15-minute train ride to the well-connected international airport of Brussels. Leuven is a very pleasant place to live where walking and cycling win from car driving.

Project

We have an open position for a PhD student in the context of a larger project entitled “The domain-specific and domain-general cognitive and neural processes underlying human success and failure”. The larger project is a collaboration between the research teams of Hans Op de Beeck (www.hoplab.be ), Céline Gillebert (www.neuropsychologylab.be ), Bert De Smedt (https://ppw.kuleuven.be/pserg/psergstaff/00040938/ ), and Kobe Desender (www.desenderlab.com ). In this PhD project, we will use computational modeling and cognitive neuroscience tools to investigate how domain-specific models of human vision, such as deep neural networks, can be enhanced with domain-general processes such as metacognitive confidence or working memory. The ultimate goal is to develop computational frameworks that provide a good mechanistic description of domain-specific and domain-general features of human cognition. Although the research will mostly focus on computational modeling, experimental studies using psychophysics and neuroimaging work (fMRI/EEG) can also be implemented to validate novel predictions from the modeling.

Profile

We look for highly motivated candidates that have (or will have) a master in a relevant discipline (e.g., computer science, cognitive neuroscience, experimental or mathematical psychology) and expertise in computational methods and cognitive neuroscience. A quantitative background and good programming skills (e.g. R, Python, Matlab) are therefore essential. Further assets are a creative mind, good problem solving skills, and a collaborative and collegial attitude. The position is funded for 4 years. The starting date would ideally be around September-November 2025. The net amount of the salary will be highly competitive internationally and in accordance with the University fellowship scales for PhD researchers. 

Offer

The position is funded for 4 years. The starting date would ideally be around September-November 2025. The net amount of the salary will be highly competitive internationally and in accordance with the University fellowship scales for PhD researchers. 

Interested?

For more information please contact Prof. dr. Kobe Desender, mail: kobe.desender@kuleuven.be, or Prof. dr. Hans Op de Beeck, mail: hans.opdebeeck@kuleuven.be. Applications can be submitted through the electronic application system of KU Leuven, and should include a motivation letter and CV, mentioning the names and contact information of at least two referents. The submission deadline is April 21st.

You can apply for this job no later than April 21, 2025 via the online application tool

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