https://www.universite-paris-saclay.fr/en/education/master/electrical-engineering/m2-multimedia-networking#presentation
The aim of this research-oriented program is to train students to carry out research on topics related to the compression of multimedia content, the transmission of this compressed data over a network, and the development of algorithms and network architectures for fast, reliable and efficient access to this content.
This program offers fundamental training in information theory, compression, signal processing for multimedia, networks and content security. A significant part is devoted to techniques for optimising architectures for the transmission of audio-visual content. Deep learning tools for compressing, transporting and processing multimedia content are also presented.
Information
Skills
Conduct a bibliographic research on a research topic.
- Formalise a research problem.
- Apply theoretical knowledge in order to offer a solution to a research problem.
- Design simulations / experiments to highlight the performance of the solution offered.
- Demonstrate critical thinking about competing solutions and the solution offered.
- Write a review article in English presenting a bibliography, describing a problem, solutions offered and experiment results, and present this work in Englishuct a bibliographic research on a research topic.
Objectives
Audiovisual information plays an increasingly important role in our environment. Smartphones, tablets and augmented reality glasses equipped with increasingly powerful cameras and displays enable us to send and receive information via wireless networks, share content on community sites and receive geographically-related information.
Career Opportunities
Career prospects
design study engineer
Research or Design Engineer
Research & Development Engineer
Further Study Opportunities
fields of statistical learning, artificial intelligence and advanced data analysis
Engineering, research and development
Students with a 2nd year Master's degree have the possibility to pursue doctoral research.
PhD thesis
Calendar
Capacity
Available Places
Target Audience and Entry Requirements
Master's degree (Bac+4) at the time of application with prerequisites in signal processing and networks.
Application Period(s)
From 01/02/2026 to 30/06/2026
Supporting documents
Compulsory supporting documents
Copy of identity document.
Motivation letter.
All transcripts of the years / semesters validated since the high school diploma at the date of application.
Curriculum Vitae.
Certificate of English level (compulsory for non-English speakers) or GMAT / GRE test results.
Recommendation letters.
Additional supporting documents
VAP file (obligatory for all persons requesting a valuation of the assets to enter the diploma).
Document indicating the list of local M2 choices available here : https://urlz.fr/i3Lo.
Supporting documents :
- Residence permit stating the country of residence of the first country
- Or receipt of request stating the country of first asylum
- Or document from the UNHCR granting refugee status
- Or receipt of refugee status request delivered in France
- Or residence permit stating the refugee status delivered in France
- Or document stating subsidiary protection in France or abroad
- Or document stating temporary protection in France or abroad.
| Subjects | ECTS | Semester | Lecture | directed study | practical class | Lecture/directed study | Lecture/practical class | directed study/practical class | distance-learning course | Project | Supervised studies |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Refresher in source coding | 1 | Semestre 1 | 9 | 4 | |||||||
| Refresher in probability, random processes, estimation and signal processing | 1 | Semestre 1 | 15 | 3 | |||||||
| Refresher in optimization (continuous variables and discrete optimization) | 1 | Semestre 1 | 12 | 3 | |||||||
| Refresher in networking | 1 | Semestre 1 | 10 | 8 | |||||||
| Subjects | ECTS | Semester | Lecture | directed study | practical class | Lecture/directed study | Lecture/practical class | directed study/practical class | distance-learning course | Project | Supervised studies |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Content Distribution Networks: performance and models | 3 | Semestre 1 | 24 | ||||||||
| Multimedia content security: basic concepts | 3 | Semestre 1 | 24 | 0 | |||||||
| Multimedia compression | 3 | Semestre 1 | 18 | 6 | |||||||
| Mathematics of Information and Source Coding | 3 | Semestre 1 | 24 | ||||||||
| Joint project and Seminar | 3 | Semestre 2 | 6 | 19 | |||||||
| Multimedia content security: advanced methods | 3 | Semestre 2 | 24 | 3 | |||||||
| Reinforcement Learning for Multimedia Applications | 3 | Semestre 2 | 21 | 6 | |||||||
| Audio-Visual transport (principles, protocols and advanced techniques) | 3 | Semestre 2 | 21 | 6 | |||||||
| Advanced compression techniques | 3 | Semestre 2 | 21 | 3 | |||||||
| Deep Learning for Multimedia | 3 | Semestre 1 | 24 | 0 | |||||||
| UE libre | 3 | Semestre 2 | 27 | ||||||||
| Subjects | ECTS | Semester | Lecture | directed study | practical class | Lecture/directed study | Lecture/practical class | directed study/practical class | distance-learning course | Project | Supervised studies |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Internship | 26 | Semestre 2 | |||||||||