Apprentissage et détection de surcharges pour des poids-lourds en circulation autoroutière à partir de mesures dynamiques de pesage

• Conduct a descriptive analysis of available data to characterize vehicle populations and identify factors explaining measurement variability
• Implement and evaluate statistical learning methods to distinguish good and bad measurements, quantify observed dispersion, and detect overload situations
• Use techniques such as supervised or semi-supervised classification, anomaly detection, and models to associate a confidence score with each observation

• Master's level student (M2 or equivalent, M1 excluded)
• Statistics
• Probability
• Computer science
• Data analysis and mining
• Data scientist
• Machine learning
• Deep learning

Net monthly salary of 600€ + 75% of monthly RATP transport costs