*Multiscale brain rhythms under healthy and epileptic conditions: computational modeling insights for clinical applications* Neural activity in the brain operates across multiple scales, encompassing both spatial and temporal dynamics. In patients with epilepsy, however, cognitive impairments are often linked to disruptions in these neural mechanisms, particularly through interictal epileptiform discharges (IEDs). This project aims to uncover new insights into the link between electrophysiology and attention deficits, one of the most prevalent cognitive impairments in patients with epilepsy, by exploring the role of IEDs. The PhD candidate will develop a comprehensive neocortical population model. The model will be validated on electrophysiological signals recorded in epileptic patients, and its dynamics will be studied to detail the mechanisms of multiple timescale interactions giving rise to healthy and pathological activity. The research project is at the interface between computational, cognitive, and clinical neurosciences. The candidate will preferably have some background in applied mathematics or computational neuroscience/systems biology. Programming skills in Python and knowledge of dynamical systems are required. Knowledge in cognitive neuroscience, electrophysiology and/or EEG analysis would be an asset. The PhD fellow will join the Cophy Team <https://cophyteam.fr/> hosted at the Center for Neuroscience Research of Lyon (CRNL), France. The ideal start date is September 2025, with some flexibility. Candidates should send their CV, a motivation letter, contact information for 2-3 references and their master degree notes (if available) to Elif Köksal-Ersöz elif.koksal@inria.fr and Mathilde Bonnefond mathilde.bonnefond@inserm.fr until June 10th 2025. Related Publications: 1. Bonnefond M, Kastner S, Jensen O. Communication between Brain Areas Based on Nested Oscillations. eNeuro. 2017; 4(2). 2. Köksal-Ersöz E, Lazazzera R, Yochum M, Merlet I, Makhalova J, Mercadal B, et al. Signal processing and computational modeling for interpretation of SEEG-recorded interictal epileptiform discharges in epileptogenic and non-epileptogenic zones. J Neural Eng. 2022;19(5):055005. 3. Köksal-Ersöz E, Yochum M, Benquet P, Wendling F. eCOALIA: Neocorticalneural mass model for simulating electroencephalographic signal, SoftwareX. 2024, 28: 101924. 4. Thieux M, Jung J. *et al.* BLAST paradigm. Epilepsy & Behavior. 2019 *;* 99: 106470.