Post-Doctoral Research Visit F/M Learning crowd dynamics from real-world data

Develop data-driven models of collective human behaviour in the VirtUs team’s FOUL-X project. Explore generative, imitation-learning and physics-informed approaches using real pedestrian trajectories, adapting models across sites and limited datasets. Work closely with the project’s data-acquisition researchers and evaluate simulation quality. The advertised start is 1 January 2027 and gross monthly pay is EUR 2,788.

PhD or equivalent, machine-learning expertise and Python skills. Experience with deep learning, generative or imitation models and interest in motion or human-behaviour modelling are relevant. Scientific communication in English is required. Apply online with a CV, cover letter and any recommendation letters. Appointment may require ministerial authorization for a restricted research area (ZRR).