We welcome students with a background in neuroscience, cognition, engineering or imaging for performing internships in our group. Internships typically last 6 months or more. During the internship, you will work closely together with one of our PhD students or postdocs, and be involved in one or more aspects of performing research: planning, data acquisition, data analysis and reporting. Most internships will involve either fMRI (3T and/or 7T) or electrocorticography (ECoG).
– How to optimally use the organization of the sensorimotor system for BCI purposes
– Cognitive BCIs
– The relationship between the fMRI BOLD signal and the underlying neuronal activity
– Function mapping in epilepsy patients
The following student projects are currently available:
|Domain/tags||Research question||Description||Data modality (division new/existing/literature)||Supervisors||Duration||Starting date||Desired skill set|
|ECoG, semantics, computational modeling||What is the temporal dynamics of the semantic encoding in the brain?||In this project we plan to investigate the temporal evolution of the semantic encoding in the brain. A computational model of word semantics will be fit on the ECoG data. The model fit at different time points will be compared. This project will contribute to our understanding about how the brain encodes word meaning.||Existing ECoG data (data analysis only)||Julia Berezutskaya, PhD student||9 months||Immediately||Machine learning, MATLAB/Python, data analysis|
|Functional MRI of Premature Infants||Design of tools for brain segmentation, normalization, etc.||Functional MRI is an increasingly used tool in research and clinical settings. Besides for adults, the technique is used nowadays also for mapping brain functions in children. Several reports even indicate that fMRI is feasible for infants, including neonates and prematurely born babies. In most cases, fMRI in these groups will involve passive tasks during natural sleep or sedation. Because of the size of the infant’s brain, standard tools for, for example, brain segmentation into ROIs (to be able to compute fMRI activation in each of these ROIs) and normalization (necessary for averaging over subjects) are not adequate and analysis of infant fMRI data will require dedicated tools.|
We are looking for an MSc student in (biomedical) engineering, artificial intelligence, computer science, or comparable training, with an interest in medical image analysis and deep learning to design tools for this analysis.
|fMRI||Ivana Isgum, Mariska van Steensel||Min. 6 months||Immediately||interest in medical image analysis and deep learning|
Students looking for an internship or a literature thesis project within these topics or a related subject, are welcome to contact us via this website: send an e-mail