Machine learning for time series prediction in environmental sciences

The internship will be done at the Computer Science Lab of Tours University (LIFAT, EA 6300), Université de Tours, 64 avenue Jean Portalis, 37200 Tours, France ;
in the Pattern Recognition group: RFAI (Reconnaissance de Formes et Analyse d’Images)
http://www.rfai.li.univ-tours.fr/

*** Context:

The internship takes place in the JUNON project, driven by the BRGM, and granted by the Centre-Val de Loire region. The main goal of JUNON is to elaborate digital services through large scale digital twins in order to improve the monitoring, understanding and prediction of environmental resources evolution and phenomena, for a better management of natural resources. JUNON will focus on the elaboration of digital twins concerning quality and quantity of ground waters, as well as emissions of greenhouse gases and pollutants with health effects, at the scale of geographical area corresponding to the North part of the Centre-Val-de-Loire region.

*** Goals:

The Master Thesis/internship position will be focused on the prediction of water resources and pollutants in the air. 

The goal will be to benchmark state of the art time series approaches and to propose new methods adapted to the specificities of the environmental data studied (multivariate time series). The benchmark on water resources relies on complex data with different seasonality and frequencies. Forecasting must be from short term to long term predictions. Regarding air pollutants, the benchmark is still to be elaborated.

Profil: Academic level equivalent to a Master 2 in progress or Engineer in its 5th year, in computer science 

Skills:

- a good experience in data analysis and machine learning (in python) is required

- some knowledge and experiences in deep learning and associated tools is required

- some knowledge in time series analysis and forecasting will be highly considered

- curiosity and ability to communicate and share your progress and to make written reports and presentations

- ability to propose solutions 

- autonomy and good organization skills