AI-Driven and Industry 4.0 enabled Frameworks for the Decarbonization of Automotive Industrial Production Sites in Morocco

This PhD project addresses the urgent need for pragmatic and operational decarbonization solutions for Moroccan automotive manufacturing sites in a context of increasing carbon taxation, stricter international sustainability requirements, and rising energy costs. While decarbonization strategies are widely discussed at policy and corporate levels, Moroccan industrial actors still lack scientifically grounded, data-driven, and context-adapted methodologies capable of translating carbon reduction objectives into actionable decisions at the plant and process levels.

The research will adopt a rigorous industrial engineering approach, combining a benchmark of international best practices in Industry 4.0 and AI-enabled decarbonization with an in-depth analysis of energy and material flows in Moroccan automotive production systems. Based on this benchmark and field diagnostics, the thesis will develop pragmatic frameworks and AI-driven decision-support tools for carbon-aware production planning, energy management, and investment prioritization. The proposed solutions will be validated through industrial case studies to assess their environmental impact, economic viability, and deployability, with the objective of providing Moroccan automotive companies with robust, scalable, and industry-ready tools to support an effective transition toward low-carbon manufacturing.

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

• Perform a benchmark of Industry 4.0 and AI-based decarbonization practices in manufacturing particularly automotive industry.
• Analyze and model energy and material flows in automotive value chains.
• Develop AI-driven decision-support frameworks for the decarbonization of automotive industrial production sites in Morocco.
• Implement and validate the proposed approaches through industrial case studies.
• Publish research results in peer-reviewed scientific journals and contribute to the valorization of UEMF’s research activities.

Candidate Profile

The candidate must hold an Engineering degree or a Master’s degree in one of the following fields:

• Computer Science and/or Artificial Intelligence (data science, machine learning)
• Industrial Engineering and Supply Chain Management
• Operations Research and Optimization
• Renewable Energy and Environmental Technologies

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. Asmae ABADI – a.abadi@ueuromed.org