PhD student - intracranial human data BCI; RIBS lab

In the Utrecht-BCI lab of the department of Neurology and Neurosurgery, a position is available for a PhD student to work on a project on development of an EEG-based eligibility assessment tool for implantation of Brain-Computer Interfaces.

The PhD candidate will join the ALPACA project (Accessible Low-Burden Assessment of Cortical Activity for Implanted BCI Candidacy in Quadriplegic Cerebral Palsy), an innovative initiative aimed at expanding access to implanted Brain-Computer Interfaces (iBCIs) for people with quadriplegic Cerebral Palsy (quad

CP). Although the field of iBCIs is advancing rapidly, individuals with quad

CP are often overlooked due to unverified assumptions about their ability to generate usable brain signals. ALPACA seeks to address this gap by developing and validating a non-invasive, easy-to-use EEG-based assessment tool to determine iBCI eligibility. The PhD candidate will acquire and analyze scalp electroencephalography (EEG) and 3 Tesla functional magnetic resonance imaging (fMRI) data from both healthy controls and individuals with Cerebral Palsy (CP), with the goal of gaining insight into the relationship between EEG and fMRI signals and identifying the most informative EEG features for predicting fMRI activity patterns.

These findings will inform the development of a validated EEG protocol, analysis pipeline, and eligibility criteria for iBCI control, which will be integrated into a standalone software package suitable for broad application in research and clinical iBCI evaluations.

The RIBS lab focuses on new neuroscientific methods for the diagnosis and support of people with neurological disorders. The team is highly multidisciplinary, with currently 8 senior scientists, 5 PhD students, 5 support staff, 3 software developers and a varying number of Master students. The members have backgrounds in neuroscience, psychology, biology, physics, computer and data science, and operate as a team with complementary skills and roles.

The common aim the team is committed to, is to translate neuroscientific and technological advances to new solutions for people with severe disabilities. Available techniques include 256-channel EEG systems for intracranial (ECoG, SEEG) recordings, 64-channel EEG system for scalp-EEG recordings, fMRI (1.5, 3 and 7T human Philips systems), 256-channel recordings in patients during awake neurosurgery and neurodevices with up to ECoG 128 electrodes implanted in people with severe motor impairments.

• have had formal university training in in biomedical engineering, bioengineering, biomedical technology, technical medicine or similar;
• have demonstrated experience in analyzing neural data, particularly EEG, and preferably also fMRI, including signal processing, feature extraction, machine learning and statistics;
• be proficient in Matlab and/or Python;
• be able to translate research findings into a practical software tool;
• be comfortable in working with clinical populations;
• enjoy working in a multidisciplinary team;
• have strong organizational skills;
• have excellent spoken and written communication skills;
• be fluent in English and Dutch (or be willing to learn to speak Dutch within the first year of the appointment).

Previous experience with brain-computer interfaces, multi-modal data integration or neurophysiology is considered an advantage.