Forward-Looking Process Mining - Automatic Construction of Simulation Environments from Process Data

This PhD seeks to revolutionize traditional methods of process mining and simulation model creation by developing a human-centered framework that extracts Discrete Event Simulation (DES) models directly from event logs. Current approaches are inefficient, heavily reliant on manual efforts, and lack evidence-based accuracy. This project aims to address key scientific challenges by integrating domain expertise with AI-driven algorithms to deliver accurate, automated, and FAIR (Findable, Accessible, Interoperable, Reusable) simulation models. The forward-looking perspective offered by this approach moves beyond analyzing historical data to combining predictive simulation for continuous process improvements.

Host Organization: Laboratoire Génie de Production (LGP) - ENIT, Université de Technologie de Tarbes (UTTOP), France Research Group: PICS (Planification, Interopérabilité, et Coordination pour les Systèmes Dynamiques) Supervisors: Dr. Sina Namaki Araghi (Lead Supervisor), Prof. Bernard Archimède (Co-Supervisor)

 We are seeking a highly disciplined individual with the following qualifications:
Master's or Engineering degree in Computer Science, Applied Mathematics, or Industrial Engineering with a specialty in System Analysis.