Networks and Distributed Systems

Explore the programs and courses offered by Networks and Distributed Systems

Browse Programs Admission Information

Program Overview

Global Objective of the Doctoral Project

The overarching goal of this doctoral project is to explore the convergence of Artificial Intelligence (AI), Big Data, and next-generation network technologies (5G+, 6G, Edge and Cloud Computing) to enhance the design, performance, and security of Distributed Networks and Systems. It aims to tackle critical challenges in intelligent connectivity, autonomous systems, and real-time distributed intelligence in strategic domains such as smart healthcare, emergency response, smart agriculture, connected vehicles, and cyber-physical systems.

The project will focus on designing scalable architectures, adaptive protocols, and intelligent services leveraging:

  • AI-driven resource allocation and optimization
  • Edge intelligence for low-latency and context-aware decision-making
  • Big Data Analytics across distributed infrastructures
  • Secure communication protocols for IoT, 5G/6G, and vehicular networks
  • Resilient systems for disaster recovery and mission-critical operations

This research aligns with the vision of Industry 5.0 and University 4.0, promoting human-centric and sustainable technological innovation. By enhancing distributed intelligence and connectivity in heterogeneous environments, the project will contribute to the digital transformation of sectors like e-health, smart mobility, intelligent agriculture, and public safety.

Teaching Language : English

Curriculum Highlights

Core Courses

During the initial years of training, the PhD student is required to attend core courses that support their scientific research and provide them with modern methodological and technical tools. The core courses include:


  • AI for Networking Systems
  • Distributed Systems and Cloud Infrastructures
  • 5G+/6G Technologies and Applications
  • Big Data in Distributed Environments
  • Research Methodology and Scientific Writing
  • Cybersecurity and Trust in Distributed Systems
  • Edge Computing and Intelligent IoT


Advanced Topics

AI & Networking

  • AI-driven network management and optimization
  • Federated and decentralized learning models
  • Self-organizing and self-healing networks

5G+/6G Applications

  • Network slicing and orchestration
  • Ultra-reliable low-latency communication (URLLC)
  • Smart city and connected vehicle infrastructures

Big Data & Edge Analytics

  • Data fusion in heterogeneous sensor networks
  • Distributed stream processing frameworks (Apache Kafka, Spark)
  • Context-aware services and real-time decision systems

Cybersecurity in Distributed Systems

  • Intrusion detection using AI
  • Secure communication protocols in mobile and IoT environments
  • Blockchain and decentralized identity verification

Smart Infrastructure Applications

  • Smart emergency and disaster response systems
  • Intelligent traffic and vehicular communication (V2X)
  • Smart agriculture and precision farming with distributed sensing

Societal and Ethical Dimensions

  • Privacy-preserving AI and data governance
  • Environmental sustainability in large-scale digital systems
  • Ethical deployment of intelligent distributed infrastructures


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Admissions Information

Language of Instruction: English (Proficiency in French and Arabic is a plus)

Admission Requirements:

  • A Master’s degree in Computer Science, Networks, or related fields
  • Academic transcripts and degree certificate
  • A preliminary research proposal aligned with the project themes
  • A detailed academic CV
  • A motivation letter describing your interests and objectives

Selection Process: Evaluation of the application file and a remote interview

Duration: 3 to 5 years based on research progress

Supervision: Provided by experts in Distributed Systems, Networking, and AI

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