A digital mobility marketplace for optimized urban transport chains

Urban sprawl and economic development are placing increasing pressure on urban road infrastructures and public transport systems, bringing the issue of mobility to the forefront—not only in terms of performance, but also of sustainability. Conventional traffic models do not sufficiently account for the varying levels of accessibility offered to users, which are themselves a major driver of travel demand, particularly for passenger transport.

As a result, non-linear phenomena such as congestion emerge and become increasingly problematic in an era that requires efficient exchanges. Transport users spend and lose more and more time, which is interpreted as a cost through the concept of the value of time. This complexity is further amplified by the fact that transport is, in essence, a service of variable quality depending on traffic conditions.

Within this doctoral research project, based on origin–destination field surveys conducted in the city of Casablanca, we aim to deploy innovative solutions to define mobility in a more efficient and intelligent way through the use of new data protocols, advanced data processing and analysis, and, more specifically, Artificial Intelligence (AI) techniques based on powerful Machine Learning algorithms. These technological innovations will simultaneously reshape both transport demand and the means of satisfying it, creating significant opportunities to address current mobility challenges.

In particular, the application of AI to mobility—especially through artificial neural networks—seeks to overcome challenges related to increasing travel demand, traffic flow management, and environmental degradation by internalizing the negative externalities of transportation.

These intelligent transport system techniques will enable new optimization possibilities and open up decision spaces that are currently underexplored, such as real-time schedule shifts and modal transfers.

The project therefore aims to contribute to the development of a new generation of intelligent models capable of addressing congestion problems and to propose appropriate policy instruments, such as dynamic pricing mechanisms.

Ultimately, based on the developed modeling framework, the project will lead to the creation of a next-generation, intermodal Intelligent Personal Travel Assistant (IPTA), capable of providing users with optimized travel chains that minimize the generalized cost of any desired origin–destination trip.

Research Environment

Candidates are expected to carry out their research full-time within the structures of the Euromed University of Fes.

PhD Student’s Responsibilities:

• Conduct a structured benchmark of international best practices in low-carbon and resilient sourcing and logistics, including Industry 4.0 and data-driven approaches.
• Model sourcing and inbound logistics processes integrating carbon footprint, risk, and operational performance indicators.
• Develop optimization and decision-support frameworks for supplier selection, logistics network design, and sourcing strategy definition under carbon and resilience constraints.
• Implement data-driven or analytical models using real or realistic industrial supply chain data.
• Validate the proposed approaches through industrial case studies with Moroccan manufacturing companies.
• Publish research results in peer-reviewed scientific journals and contribute to the valorization of UEMF’s research activities.

Candidate Profile

• Degree in Statistics and Applied Economics (Engineering or equivalent), with a focus on economic modeling and econometric analysis (programming skills are highly desirable) or Master’s degree in Applied Mathematics or Industrial Engineering, with strong background in operations research (optimization, simulation, and algorithms) and programming.
• Strong interest in transportation and logistics.

The application file must include the following documents:

• CV with photo
• Cover letter
• Copy of diplomas
• Copy of academic transcripts
• Copy of CIN/Passport

Submission of the Application File:

The application file must be sent to the Doctoral Studies Center (CEDoc) of the Euro-Mediterranean University of Fes by email no later than February 14, 2026, to the following email address:

Euromed-CEDoc@ueuromed.org

For More Information

Administrative Affairs Officer of the CEDoc:
Ms. Boutaina Jai Mansouri – b.jai-mansouri@emadu.ueuromed.org

Director of Research and of the CEDoc:
Prof. Abdelghafour Marfak – a.marfak@euromed.org

Thesis Supervisor

Prof. Othmane Benmoussa – o.benmoussa@ueuromed.org