Applications of machine learning tools in predicting the impacts of climate changes on water resources

In the context of climate change and anthropogenic impacts that constitute a major risk of depletion of drinking water reservoirs and in order to assess this risk in the short and long term,  the M2C-CNRS laboratory of the University of Rouen launch a project on the effectiveness of machine learning tools (CNN, LSTM, SVM, etc.) in the prediction and assessment of climatic and anthropogenic impacts on water reservoirs (aquifers and rivers) at the scale of metropolitan France. This project is proposed as a PhD thesis and we are looking for someone with skills in applied mathematics/physics/hydrology with preferably expertise in machine learning

To apply, please send a CV with your M1 and M2 grades

https://m2c.cnrs.fr/

Nous recherchons des candidats ayant une solide formation en mathématiques/physique appliquées/sciences des données afin d'explorer l'efficacité de nouveaux outils d'apprentissages automatiques pour prédire l'impact des changements climatiques sur les ressources en eau.  Les candidats doivent être titulaires d'un master 2/diplôme d'ingénieur en mathématiques appliquées/programmation informatique (Matlab, Python, R/Artificial intelligence.

Pour postuler, veuillez envoyer uniquement votre CV avec les notes M1 et M2.