Job offer

Organisation/Company Gustave Eiffel University Department AME Research Field Computer science » Other Engineering » Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Apr 2026 - 23:59 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 7:42 Offer Starting Date 1 Oct 2026 Is the job funded through the EU Research Framework Programme? Other EU programme Reference Number Projet-ANR-25-CE Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Université Gustave Eiffel (France) invites applications for a fully funded PhD position in Artificial Intelligence, Machine Learning and Sensor Fusion for the analysis of human walking dynamics in urban environments. The position is offered within the ANR CITY-STEP project at the GEOLOC laboratory, an internationally recognized research group working on pedestrian navigation, inertial sensors and smart urban mobility.

The PhD project aims to develop a personalized and environment-sensitive walking model capable of describing how urban morphology influences pedestrian movement at the step level. Using a multi-sensor experimental platform combining inertial sensors, GNSS, camera and eye-tracking, the doctoral candidate will collect and analyze motion data in real urban environments.

The research will focus on extracting individualized walking signatures from sensor data, detecting locomotor events, and modeling the influence of environmental characteristics such as slope, street layout, intersections or visual stimuli. The work will combine signal processing, machine learning and sensor fusion techniques to build a multi-scale model linking micro-locomotor dynamics to urban morphology.

The PhD will be conducted at the GEOLOC laboratory (Université Gustave Eiffel) in collaboration with the AAU team at École Centrale de Nantes.

Profile: MSc in Computer Science, Robotics, Signal Processing, Biomechanics, Artificial Intelligence or related fields. Experience in Python, data analysis, machine learning or inertial sensors is appreciated.

Keywords: Artificial Intelligence, Machine Learning, Sensor Fusion, Pedestrian Navigation, Inertial Sensors, Human Motion Analysis, Urban Mobility.

Application: Applicants must submit by email a detailed CV, a cover letter explaining their interest in the subject, one or two references, and if applicable, a Master's thesis or a significant internship report.

Full PhD Offer Description

We are looking for a candidate who is highly motivated by interdisciplinary research and interested in working at the intersection of signal processing, artificial intelligence, biomechanics, and urban mobility.

Education: Master’s degree (or equivalent) in navigation/geomatics, signal processing/data science, computer science/artificial intelligence, biomechanics, or a related discipline. Excellent academic performance is expected.

Scientific and technical skills

• Solid foundation in signal processing (time/frequency analysis, filtering, event detection)
• Knowledge of machine learning (classification, supervised/unsupervised models)
• Interest in multi-sensor systems and experimental data
• Previous experience in one of the following areas would be an asset: analysis of data from inertial sensors (IMU), human activity recognition, biomechanics of walking, sensor fusion, and computer vision

Personal skills

• Interest in experimental work in real-world conditions
• Ability to work in an interdisciplinary team
• Initiative, autonomy, and scientific rigor
• Good writing skills in English

Languages ENGLISH Level Excellent

Additional Information

• International environment
• Discounted public transportation
• Cultural and sporting activities

Start of thesis: September/October 2026

Duration: 36 months

Funding: ~€3,200 gross monthly, Doctoral contract funded as part of the ANR City-Step project