Post-Doctoral Research Visit F/M Analysis of mobile network traffic in atypical situations

Context
A post-doctoral fellowship is available in the Inria Agora team in the Lyon center. The post-doctoral fellow will collaborate with Dr. Razvan Stanica (
http://perso.citi.insa-lyon.fr/rstanica/
) from the Inria Agora team and with a multidisciplinary team of researchers in computer science, transportation, and geography. This position is funded in the context of the National French PEPR projects on "Natural Risks" and "Mobility Digitalization".
Inria Agora is a joint team with INSA Lyon, one of the most prestigious engineering schools in France. Teaching involvement and student supervision are possible (but not mandatory) at INSA Lyon.
Assignment
The recruited person will conduct research on the topic of mobile data analysis. This is data collected by mobile network operators, covering large areas and populations, with numerous possible application, such as energy-efficient network resource allocation (e.g., 5G/6G), epidemic propagation, transportartion system design, user recommendation systems, urban planning in smart cities, or ride-sharing.
The researcher will work on uniquely-rich datasets collected by French mobile operators, with a focus on atypical situations, such as holidays, harsh weather conditions, natural disasters, major social and cultural events. The objective is to understand the behaviour of mobile network users, in terms of mobility and service demand, during such atypical events, find spatio-temporal patterns and compare this with the behaviour observed in normal conditions.
Main activities
Propose new analytical tools and research questions exploiting the mobile phone data. We dispose of uniquely rich datasets, rarely available to the academic community. The recruited person will have a lot of autonomy in exploring new ideas building on these datasets.
Extraction of repetitive patterns from mobile telephony data collected by operators, in order to construct typical user and network behaviour. This behaviour will be used as baseline for comparison with the user behaviour during atypical situations.
Spatio-temporal characterization of different types of atypical situations recorded in the data. A special attention will be given to extreme weather events, especially flooding events recorded in the south of France.
Advise undergraduate and Master students for research-related projects.
Skills
The candidates should have a master or PhD degree on network and/or data-related topics. Experience with data analysis in Python or R is expected.
Good personal and project management skills are required to function in this multi-disciplinary multi-team project.
Working language is English.