systèmes intelligents et apprentissage automatique

Program Overview

The Doctoral Training Program in Intelligent Systems and Machine Learning at the University of Ghardaïa is a cutting-edge initiative launched under the framework of the regional doctoral school for the academic year 2024/2025. This PhD program is designed to train high-level researchers in one of the most dynamic and impactful areas of computer science—artificial intelligence (AI)—with a particular emphasis on intelligent systems and automated learning. The program addresses national strategic needs by supporting the development of digital innovation, enhancing AI expertise within academia and industry, and ensuring continuity with the existing Master's program (SIEC) focused on knowledge extraction systems. It seeks to build a generation of experts capable of designing, developing, and deploying intelligent solutions across a variety of sectors including healthcare, cybersecurity, robotics, and natural language processing

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Curriculum Highlights

Core Courses

The program includes robust technical and scientific foundations, supported by qualified faculty and industry experts. Key courses and training units include:

Core Topics:
Deep Learning Architectures
Vision Transformers and Medical Imaging
Cybersecurity and AI-based Intrusion Detection
Multimodal Data Fusion
Explainable AI (XAI) and Trustworthy Models
Natural Language Processing (Arabic and multilingual context)
Supervision and Expertise:
Faculty includes professors and associate researchers from national institutions and international universities, with expertise spanning AI, machine learning, NLP, computer vision, medical imaging, and cybersecurity.
Research and Thesis Projects cover strategic areas such as:
Lifelong Learning and Continual AI
Advanced Plagiarism Detection in Arabic using Large Language Models
Multimodal Analysis for Alzheimer’s Prediction
Deep Community Detection in Evolving Networks
Explainability in Healthcare AI Systems

Advanced Topics

Doctoral candidates may specialize in advanced research domains including:

Lifelong Artificial Intelligence: Focused on continual learning, memory-augmented architectures, and adaptability in non-stationary environments.
Explainable AI in Medicine: Creating transparent, interpretable models for use in diagnosis and treatment.
Cybersecurity Systems: AI-powered intrusion detection/prevention using deep learning, federated learning, and lightweight architectures.
Multimodal Analysis: Combining neuroimaging, genetics, and clinical data for predictive healthcare models (e.g., Alzheimer’s).
Arabic NLP: Leveraging deep neural models and LLMs to detect advanced plagiarism in academic texts.
Zero-shot and Few-shot Learning: Enhancing CLIP models and object detection networks for cross-domain biological image recognition and medical imaging tasks.
Vision Transformers: Comparative studies of self-supervised ViT architectures in real medical datasets using frameworks like DINO.

This research-intensive environment is supported by state-of-the-art laboratories, computational resources (including machine learning workstations), and strategic partnerships with national and international institutions such as SONATRACH, URAER, Huawei Algeria, and Canadian universities

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Admissions Information

Applicants must hold a Master’s degree in Computer Science or a closely related field. The program seeks motivated candidates who demonstrate strong academic performance, research potential, and alignment with the AI research themes outlined in the program. The selection process may include dossier evaluation, interviews, and prior research experience consideration. The doctoral program is open to students across Algeria, and particularly encourages candidates with backgrounds in intelligent systems, data science, and applied machine learning to apply

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