POSTDOCTORAL FELLOWSHIP “DATA SCIENCE APPLIED ON POSITIONING ANOMALY DETECTION AND UNCERTAINTY ESTIMATION”
Financed by the French Research Agency (Agence Nationale de la Recherche), this postdoctoral research fellow position will work in the framework of the project ReSilientGAIA (Reliable Positioning System for Soft Mobility Safety Enhancement with a Green AI Approach). The objective of this project is to add safety control in a new reliable positioning algorithm based on multisensory fusion for soft mobility users (pedestrian, bikes, e-scooters, etc). The sensors considered in this project include Global Navigation Satellite Systems (GNSS), Inertial Navigation System (INS), magnetometer, barometer and possibly a camera. Our ambition is to design new approaches based on AI to build physical models that describe the signal perturbations in complex urban environments. By improving the safety and reliability of the positioning system for soft mobility, this project contributes to the mobility transition strategy toward lower carbon emissions.
Type de poste
Chercheur(e)
Localisation
Campus de Nantes
Missions principales
Main tasks:
The postdoctoral fellowship will work on the following missions:
- Vehicular AI model training for GNSS measurement anomaly detection and positioning uncertainty estimation. To do this, the existing labeled dataset will be used in priority. Potential environmental features (such as urban morphological indicators) will be considered using the 3D city model.
- Propose an approach of automatic data augmentation and continuous learning for the pre-trained vehicle anomaly detection model.
- Soft mobility data labeling technique development using fisheye camera: propose a method to further evaluate and improve the accuracy of the labeling technique developed in [1], which uses image segmentation and satellite projection.
- Once the labeling technique is developed, a soft mobility multiple-sensor dataset will be constructed. The soft mobility considered in the project includes mainly pedestrians, bikes and e-scooters.
- Analyze the feasibility and the possible approaches of the transfer learning between vehicle and pedestrian.
The research work will be co-supervised by the researchers from GEOLOC laboratory at the University Gustave Eiffel and the AAU-CRENAU laboratory of CNRS. The candidate should hold a PhD degree in data science, applied mathematics or computer science. Specialization in Artificial Intelligence (or statistical learning methods) and experience in their application to one or more of the following fields are required: Signal processing, Computer vision, Geomatics, and Navigation.
Contract: Fixed-term contract of 24 months
Monthly Salary: 2 794.12€ - 3 019.45€ (according to experiences)
Catégorie
A
Affectation
AME-GEOLOC (campus Nantes)
Mission d’encadrement
oui
Conduite de projet
oui
Savoirs
Knowledge
- Data Science
- Signal/image processing
- AI (time series analysis)
- English: fluent
Savoir faire
Skills / Know-how
- Coding in Python, matlab coding
- Scientific writing
Savoir être
Soft skills
- Communication
- Teamwork
- Organization and rigor
- Capacity of proposal
Nombre de postes à pourvoir
1
Personnes à contacter :
Envoyer CV et lettre de motivation à : rochdi.saffi@univ-eiffel.fr et lois.sanchez@univ-eiffel.fr
Contact: ni.zhu@univ-eiffel.fr