Modern soft matter research is increasingly driven by high-resolution, high-throughput experimental techniques, and the first theme, Microscopy & Imaging, will introduce participants to state-of-the-art tools that allow direct visualization of structure, dynamics, and function across scales, from molecular assemblies to mesoscopic collective behavior.

The module will begin with elastic scattering techniques: Small-Angle X-ray Scattering (SAXS), Small-Angle Neutron Scattering (SANS), and Static Light Scattering (SLS), which provide reciprocal-space access to nanoscale organization and correlations, along with a brief introduction to inelastic scattering to highlight how dynamical information can be extracted. Real-space imaging will be discussed starting from the Abbe theory of image formation, establishing fundamental limits of optical resolution. Contrast-enhancing optical methods such as Phase Contrast, Differential Interference Contrast (DIC), and Dark Field microscopy will be introduced for visualizing transparent and weakly scattering soft materials. Fluorescence microscopy and super-resolution techniques will be covered to illustrate selective imaging and nanoscale visualization beyond the diffraction limit. The module will also include Atomic Force Microscopy (AFM) for nanoscale imaging and mechanical characterization, Optical Tweezers for force manipulation and micromechanical measurements, and Differential Dynamic Microscopy (DDM) as a powerful bridge between imaging and scattering for extracting dynamical information from time-resolved microscopy data.

This mini-school on Active Matter will provide a broad and integrated introduction to the field, encompassing both fundamental concepts and recent advances in nonequilibrium systems.

The programme will place strong emphasis on experimental realizations of artificial microswimmers, including Janus colloids and active droplets, along with state-of-the-art techniques for particle tracking and micro-PIV to quantitatively characterize their active dynamics. In addition, the mini-school will cover the fundamentals of rheology and highlight recent developments in the rheology of active suspensions. The lectures will also explore key phenomena such as interactions, motility-induced phase separation (MIPS), the distinction between dry and wet active matter, and the role of hydrodynamic and phoretic interactions to determine emergent dynamics of many active particles. By bridging theory, simulations, experiments, and rheological perspectives, the mini-school aims to equip participants with a coherent framework to understand pattern formation, phase behavior, mechanical response, and emergent phenomena in active matter.

The Computational Soft Matter theme will introduce modern theoretical, computational, and data-driven approaches to understanding complex soft systems across scales.

The program will cover the mathematical foundations of neural network–based machine learning, complemented by hands-on sessions and case studies demonstrating ML applications in soft matter. A key focus will be on linking microscopic structure to dynamics, showing how simple structural information can be used to construct predictive order parameters and how these ideas connect naturally to machine-learning–derived descriptors.

The theme will also highlight emerging directions where learning is embedded in physical matter, including material networks that perform machine-learning–like tasks through local learning rules, offering brain-inspired and energy-efficient alternatives to conventional artificial neural networks.

The program will conclude with recent advances in dilute polymer solution rheology, emphasizing the interplay between polymer kinetic theory and continuum mechanics, insights from single-molecule dynamics into challenges such as the high Weissenberg number problem, and the central role of hydrodynamic interactions, incorporated through closure approximations and multiscale simulations.