Call for applications for a fully financed PhD fellowship

A fully financed PhD fellowship is available at the Center for Music in the Brain (MIB), Department of Clinical Medicine, Aarhus University (AU), in connection with Associate Professor Leonardo Bonetti’s DFF Sapere Aude grant.

Project description

This PhD project aims to investigate functional brain networks using stereo-electroencephalography (SEEG) data acquired from patients with epilepsy. SEEG is an invasive neurophysiological technique that records electrical activity from deep and cortical brain structures via surgically implanted electrodes, enabling direct measurement of local field potentials (LFPs) from neural tissue. Clinically, SEEG is primarily used in the pre-surgical evaluation of epilepsy patients to precisely localize seizure foci. However, the richness of SEEG data also offers a unique opportunity to advance our understanding of both general brain network organization and epilepsy-specific neural dynamics.

In this PhD project, the candidate will leverage SEEG datasets in combination with recently developed brain network analysis tools to pursue two main objectives.

1) Network characterization of epileptic activity; the project will develop a network-level understanding of seizures and other pathological electrophysiological events recorded in SEEG data. The aim is to identify novel network signatures of epilepsy that may provide insights of direct clinical relevance, including potential implications for diagnosis and treatment planning.

2) Functional brain networks supporting cognition; the project will also analyze SEEG data acquired while patients perform memory tasks, with a particular focus on auditory and visuo-spatial domains. These analyses will be used to characterize the functional network configurations of brain regions sampled by SEEG electrodes during cognitive processing.

By integrating these two perspectives, the project will provide a comprehensive view of brain network organization in epilepsy, as well as in core human cognitive processes.

The project will primarily involve advanced data analysis, combining established methods from invasive neurophysiology, signal processing, and multivariate statistics. The candidate will also apply and further develop novel network analysis methods created at the Center for Music in the Brain, including FREQNESS and BROADNESS, to derive physiologically meaningful functional brain networks.

The PhD study will include participation in PhD courses, writing scientific articles and a PhD thesis, teaching and knowledge dissemination activities, active participation in national and international scientific meetings.

Qualifications

 

Essential criteria:

• A master’s degree (120 ECTS), typically in the field of neuroscience, cognitive science, physics, engineering, medicine, psychology or other relevant education (candidates currently enrolled in a master's programme may apply if they are expected to submit their master's thesis within 3 months from the application deadline).
• A strong interest in the cognitive neuroscience of music, data analysis and empirical research.
• Experience of conducting empirical research and data analysis.
• Strong experience with signal processing and statistical analysis in relation to neuroimaging data.
• Strong experience in computer programming (especially in Matlab and Python).
• Confidence in dealing with participants, health professionals and the wider research team.
• Excellent verbal and written communication skills (in English).
• Strong collaborative skills as the successful candidates will join a large multidisciplinary research environment.

Desirable:

• Track record of publications.

How to apply

Please submit your application via this link. Application deadline is 7 April 2026 23:59 CET. Preferred starting date is 1 June 2026 or as soon as possible thereafter.

For information about application requirements and mandatory attachments, please see our application guide.  

Further information

Please contact Associate Professor Leonardo Bonetti, leonardo.bonetti@clin.au.dk, for more information.

All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.