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InterDigital
26 oct., 2025
STAGE, Stage
InternApplied Ml Multimedia Internship Position H/F
InterDigital
Summary As an applied ML Multimedia Research Intern, you will work closely with researchers and engineers to address cutting-edge challenges in the field. You will receive dedicated technical mentorship and guidance, ensuring continuous learning and skill development throughout the internship. Each day will provide new opportunities to expand your technical expertise while deepening your understanding of the multimedia domain. Beyond technical growth, this internship will allow you to build valuable connections with domain experts and industry professionals. Depending on the outcomes of your work, you may also have the opportunity to contribute to publications, further advancing your academic and professional profile. Responsibilities List of primary responsibilities Survey the recent advances of state-of-the-art ML-based media compression technologies Conduct literature reviews and stay up to date with state-of-the-art techniques in ML-based media compression, multimedia...
Qualifications List minimum required qualifications, preferred skills, abilities, experience, and education Currently pursuing master or doctoral degree in Machine learning, multimedia, telecommunication Strong background in machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow) Experience in Python/C++ programming and working with research prototypes. Preferred knowledge on multimedia frameworks Preferred experience with multimedia libraries and frameworks such as libav, ffmpeg, GStreamer etc. Familiarity with signal processing, computer vision, or audio/video communication systems. Knowledge of neural compression methods (e.g., learned image/video compression, generative models for media coding) is a plus. Understanding of multimedia coding standards (e.g., H.264/AVC, H.265/HEVC, AV1, VVC) and compression techniques is a plus Problem solving skills Ability to collaborate with others Preferrable demonstrate expertise with proven publication or...
Durée (Mois):
6
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