Randomness is at the heart of modeling questions in the life sciences, particularly in biology, medical imaging and neuroscience. Within the Probability, Statistics and Applications team, these concerns are harmonized from both a theoretical and an applied perspective: random fields and processes, models of stochastic geometry, ergodic theory and limit theorems, stochastic algorithms, non-statistics. parametric, data analysis, statistical learning, classification and detection of breaks. This work is also developing in interaction with biology and medicine teams from the University of Poitiers and elsewhere.