Intern: Real-Time Neural Video Transport over MOQT

InterDigital CE Patent Holdings, SAS; Rennes; On-site; EUR 13,000 - 20,000; Full time

Job summary

InterDigital Rennes Lab offers an internship focusing on real-time neural video codecs and MOQT transport. You will study state-of-the-art NVC techniques, work on NMSF-based packetization, and build a reproducible MOQT testbed to evaluate latency and quality.

You will collaborate with researchers, publish findings, and contribute to an alumni Master’s thesis and presentation. Eligible Masters students in CS/telecommunications are encouraged to apply.

Qualifications

• Master’s student in computer science, telecommunications, signal processing, or a related field.
• Knowledge of computer networks, multimedia systems, video coding, machine learning.
• Programming experience, preferably in Python and C or C++.
• Ability to read and analyze technical standards and research publications.
• Familiarity with QUIC, RTP, video compression, video-quality evaluation, neural compression would be an advantage.

Responsibilities

• Review the state of the art in neural video compression, real-time media transport, QUIC, MOQT, and media packetization.
• Analyze NVC bitstreams, frame dependencies, decoder state, and transport requirements.
• Implement NMSF-based packetization and integrate the codec with an MOQT sender and receiver.
• Develop a reproducible testbed and evaluate latency, overhead, robustness, recovery behavior, video quality and computational performance.
• Analyze the experimental results and propose improvements to NMSF or an alternative packetization design.

Skills

Knowledge of computer networks

Multimedia systems

Video coding

Machine learning

Education

Master’s degree in computer science, telecommunications, signal processing, or related field

Tools

Python

C/C++

Job description

InterDigital Rennes Lab offers an internship focusing on real-time neural video codecs and MOQT transport. You will study state-of-the-art NVC techniques, work on NMSF-based packetization, and build a reproducible MOQT testbed to evaluate latency and quality.

You will collaborate with researchers, publish findings, and contribute to an alumni Master’s thesis and presentation. Eligible Masters students in CS/telecommunications are encouraged to apply.