PhD position in computational neuroscience (event-based computing / spiking networks) As part of a Marie-Curie Doctoral Network (ELEVATE <https://www.elevate-dn.eu/index.php/about/>), we are offering a PhD student position. The proposed project sits a the interface of computational neuroscience and neuromorphic computing, and is embedded within a strong network of European academic and industrial partners. ENVIRONMENT: The student will be part of the Theoretical Neuroscience lab <https://www.machenslab.org/>, led by Christian Machens, which is hosted at the Champalimaud Centre for the Unknown in Lisbon, Portugal. The Champalimaud Foundation <https://www.fchampalimaud.org/> is a private, non-profit institute with a vibrant and highly international academic community. Many groups work in the field of systems and computational neuroscience, <https://www.fchampalimaud.org/champalimaud-research> providing a stimulating and exciting work environment. The student will also interact with the training network ELEVATE <https://www.elevate-dn.eu/index.php/about/> and spend several months at Rodolphe Sepulchre <https://sites.google.com/site/rsepulchre/>‘s lab at KU Leuven, Belgium. PROJECT: Across the animal world, biological networks are made up of different types of neurons. The most prominent division is that between excitatory (E) and inhibitory (I) neurons. However, modern AI system as well as most neuromorphic systems ignore this division and assume only one type of neuron. In this project, we will study the specific functional or structural qualities arising from a division into E and I neurons, and work out any potential benefits. One key design feature of networks with E and I neurons is that they are composed of intrinsically unstable subsystems, namely recurrently connected E neurons, that are controlled and stabilized by other subsystems, namely I neurons. The benefits of designing and controlling intrinsically unstable systems have long been known to engineers in other context, e.g., the desing of modern fighter aircraft. The goal of this project is to use some of these engineering insights in order to investigate how the interplay of excitation and inhibition can be utilized to perform specific computations. Since real neurons communicate with discrete events (spikes), a key aim is to work out the distinct computational roles of inhibitory and excitatory spikes, and apply the concepts to a few example systems. TASKS: * Study the relevant background literature from both engineering and neuroscience fields. Based on geometric and analytical insights from the framework of ‘spike coding networks’, develop analytical or geometric methods to study the roles of excitatory and inhibitory spikes. Develop a few canonical systems and use numerical simulations to demonstrate the role of excitatory and inhibitory populations in computational tasks. * Publish research articles, regular participation in top international conferences to present your work. * Complete an internship at KU Leuven with Prof. Rodolphe Sepulchre * Participate in yearly retreats organized by the doctoral network participants * Support the dissemination of software tools and concepts. SALARY AND CONDITIONS: The salary and benefits will follow standard EU rules. PhD students will receive their degree from the NOVA University of Lisbon. APPLICATION: We are looking for a candidate with strong quantitative skills (e.g., degree in physics, computer science, engineering, etc.) and curiosity about how the brain works. Interested candidates should submit a detailed CV, a cover letter explaining their interest in the position (1 page), a transcript for their BSc and Msc, and the contact information of 2 references to christian.machens@neuro.fchampalimaud.org. The application process will remain open until the position is filled. We strive to build a diverse work environment and encourage applications from all qualified individuals irrespective of their gender, age, cultural background, and disability status. Only candidates shortlisted for this position will be contacted for an interview. STARTING DATE: We anticipate a start in the year 2026. The earliest starting date is January 1st, 2026.