This project aims to study intermittent collective motion (ICM), a phenomenon where groups of individuals alternate between phases of coordinated movement and disordered or resting states. Such intermittent dynamics have been observed in species like sheep and fish, revealing complex patterns that emerge from simple individual interactions. The internship will focus on modeling the consensus process that initiates and terminates collective motion phases, using a computational approach to capture the mechanisms driving these transitions. To quantify ICM dynamics, we will measure observables at both the individual and group levels: individual positions and activity patterns, and collective properties such as group displacement, cohesion, and alignment. The model will be validated against existing experimental data from groups of sheep, and simulations will be used to test how coordination depends on factors such as group size, the presence of leaders, or environmental obstacles. Ultimately, the project seeks to unveil the individual-level mechanisms responsible for the emergence of complex collective dynamics in animal groups.