Dear Colleagues, The deadline for the Cajal course in Computational Neuroscience has been extended to March 9! We look forward to seeing you in sunny Lisbon this summer! Please apply. -Maria ________________________________ From: Maria Neimark Geffen <mariageffen@gmail.com> Sent: Friday, January 30, 2026 10:21 AM To: comp-neuro@lists.cnsorg.org <comp-neuro@lists.cnsorg.org> Subject: Accepting applications: The Brain Prize Course - Computational and Theoretical Neuroscience 2026 Dear Colleagues, I’m writing as a co-director of the upcoming CAJAL Advanced Neuroscience Training Course: The Brain Prize Course - Computational and Theoretical Neuroscience 2026, now open for applications. This intensive course is a unique opportunity for early-career researchers interested in this field. Hosted at the Champalimaud Centre for the Unknown, this three-week course focuses on bridging the gap between theoretical frameworks and experimental neuroscience. It provides intensive training in neural coding, network dynamics, and advanced data analysis, combining high-level lectures with hands-on Python-based projects to model complex brain functions and interpret large-scale neuronal datasets. 📍 Location: Champalimaud Centre for the Unknown, Lisbon, Portugal 📅 Dates: 13 - 31 July 2026 ⏳ Application Deadline: 27 February 2026 🔗 Apply now: https://form.jotform.com/Cajal_training/computational-neuro2026 Course Directors * Alfonso Renart - Champalimaud Foundation, Portugal * Julijana Gjorgjieva - Technical University of Munich, Germany * Maria Geffen - University of Pennsylvania, USA * Omri Barak - Technion, Israel Institute of Technology Course Themes & Topics: * Neural Modeling & Dynamics: Mastering the mathematical foundations of brain function, from single-cell biophysical models like Hodgkin−Huxley to the complex behavior of excitatory-inhibitory networks. * Neural Coding & Data Analysis: Learning how populations of neurons represent information using advanced computational tools like dimensionality reduction to decode large-scale neural datasets. * Cognitive & Normative Theory: Exploring high-level functions through Bayesian inference and reinforcement learning to understand how the brain optimizes decision-making and motor control. Speakers include: * Larry Abbott (Columbia University, USA) * Haim Sompolinsky (Harvard University, USA & Hebrew University of Jerusalem, Israel) * Susanne Schreiber (Humboldt University of Berlin, Germany) * Francesca Mastrogiuseppe (SISSA – International School for Advanced Studies, Italy ) * Il Memming Park (Champalimaud Foundation, Portugal) * Jakob Macke (University of Tübingen, Germany ) * Wiktor Młynarski (LMU Munich – Ludwig-Maximilians-Universität München, Germany ) * Laura Busse (LMU Munich – Ludwig-Maximilians-Universität München, Germany ) * Yiota Poirazi (IMBB–FORTH, Heraklion, Greece ) * Adrienne Fairhall (University of Washington, USA) * Agostina Palmigiano (Gatsby Computational Neuroscience Unit, UCL, UK) * Joe Paton (Champalimaud Foundation, Portugal) * Dmitri Chklovskii (Flatiron Institute, Simons Foundation, USA) * Brent Doiron (University of Chicago, USA) * Gilles Laurent (Max Planck Institute for Brain Research, Germany) * Alex Cayco Gajic (École Normale Supérieure – PSL, France ) * Rafal Bogacz (MRC Brain Network Dynamics Unit, University of Oxford, UK) ________________________________ Maria Neimark Geffen, Ph.D. (she/her) Professor Co-director, Penn Computational Neuroscience Initiative Department of Otorhinolaryngology: HNS (primary) Department of Neuroscience Department of Neurology Perelman School of Medicine University of Pennsylvania 5 Ravdin 3400 Spruce St. Philadelphia PA 19104 Tel.: 215.898.0782 My zoom<https://pennmedicine.zoom.us/my/mgeffen?pwd=eWVFbUJFUGRJZ3g1eU9YZEZic2VwZz09> mgeffen@pennmedicine.upenn.edu<mailto:mgeffen@pennmedicine.upenn.edu> http://hosting.med.upenn.edu/hearing https://bsky.app/profile/geffenlab.bsky.social