Statistical Physics workshops

This workshop connects mathematical and theoretical neuroscience approaches to the dynamics of densely connected recurrent spiking networks. Mean-field methods link individual-neuron dynamics with population behaviour, while low-dimensional collective dynamics and low-rank connectivity provide complementary descriptions informed by experiments and simulations. Researchers with mathematical and physics backgrounds alternate presentations to compare these perspectives. Public research lectures run from Monday afternoon through Wednesday, followed by doctoral tutorials on Thursday and Friday at the Bernoulli Center, EPFL, Lausanne. Registration begins at 13:30 on 2 November, with the introduction at 13:45 and talks from 14:00. Tuesday and Wednesday lectures and Thursday and Friday tutorials start at 09:00. Times are Europe/Zurich, CET (UTC+01:00). Seats are limited; researchers from outside EPFL pay CHF90 and commit to attending the lecture sessions. Tutorials are restricted to PhD students. Separate registration forms for doctoral students and other researchers are linked on the official workshop page. Preparation assumes mathematics or physics at master’s level and familiarity with computational neuroscience.

Explore whether the physics of glass and jamming transitions can provide shared principles for complex matter, from amorphous solids and granular flows to living systems. The programme combines theoretical, experimental and computational approaches to nonequilibrium dynamics, structural disorder and collective behaviour. Discussions connect soft and active matter with biological processes and medical challenges, seeking research directions that cross the boundaries between physics, chemistry, materials and medicine. 14 December at 10:15 to 18 December at 12:40; Asia/Tokyo (JST, UTC+09:00). Attendance-only registration is due 30 November. Poster proposals are due 31 October, subject to capacity; oral submission and banquet booking have closed. An Indico account is required, with new accounts approved during Japanese weekday office hours.

A graduate school and research workshop examine water from molecular to planetary scales. The programme connects hydrogen bonding and quantum effects with collective dynamics, interfaces, biological function, extreme conditions and atmospheric water. Participants study first-principles simulations, machine-learned potentials and multiscale modelling. The first week provides foundational training; the second features current research, discussions and posters. Applicants should have grounding in statistical mechanics, quantum mechanics and molecular simulation or related computation. Graduate students, postdocs and early-career faculty are the main audience, with limited consideration of senior undergraduates. ICTS provides accommodation for outstation participants.

The school introduces non-equilibrium statistical physics and stochastic processes as tools for noisy, dynamic systems. Lectures cover transport, carbon nanostructures and carbon nanotubes, theoretical and experimental biophysics, and connections between non-equilibrium physics and problems spanning cosmology to living systems. It is designed for master's and doctoral students and early-career postdoctoral researchers, requiring little prior experience of these advanced topics. Participants submit poster abstracts. There is no registration fee; limited attendance grants prioritize participants from developing countries. The programme supports research training and collaboration across Africa.

The School on Analytical Connectionism is a two-week summer course on analytical tools, including methods from statistical physics and probability theory, for probing neural network models of higher-level cognition, bringing together neuroscience, psychology and machine-learning communities. The 2027 school, held in Boston from 2 to 13 August 2027, focuses on interpretability in reasoning and mathematical cognition: how children or artificial systems use and acquire mathematical concepts, how mathematical intuition and expertise develop and interact, and how studying the heuristics and abstractions that AI systems develop may deepen understanding of human mathematical cognition. The first week offers core lectures on mathematical methods for neural network analysis and on key connectionist models linked to experimental observations; the second week offers frontiers lectures. Participants also join tutorials, poster sessions and contributed talks, work in teams on research projects that they pitch in week one and present at the end, and co-author peer-reviewed lecture notes collected into a special issue. The school is directed by Erin Grant (University of Alberta & Amii) and Stefano Sarao Mannelli (Chalmers University of Technology & University of Gothenburg), with SueYeon Chung (Harvard University & Flatiron Institute) and Andrew Saxe (University College London) as advisors. Applications open on 1 February 2027 and close on 1 April 2027 (AoE); first-round outcomes are communicated on 17 May 2027.