PhD CIFRE, PhD – Deep-based reference pictures generation for video codin

InterDigital CE Patent Holdings, SAS; Rennes; Sur place; EUR 42 000 - 54 000; Plein temps

Résumé du poste

InterDigital R&I Center in Rennes, France, seeks a PhD researcher in deep-based video coding to advance 2D video coding with deep-learning methods. The project emphasizes inter-prediction improvements and standardization contributions within MPEG, JVET, and related groups.

You will build and test new algorithms in C/C++, Python and TensorFlow, collaborate with the video coding and deep learning team, and present results to journals and conferences. Fluent English is required; French is a plus.

Qualifications

• PhD or Master in CS with experience in deep learning or related fields.
• Interest in computer vision and image processing.
• Experience implementing in C/C++, Windows/Linux, Python, TensorFlow.

Responsabilités

• Follow state-of-the-art and standardization in Deep learning and Video Coding.
• Propose and implement new video coding algorithms with the team.
• Contribute to invention disclosures and standardization efforts.
• Present results in journals and conferences.

Connaissances

Deep learning

Machine learning

Computer Vision

Image processing

Communication

Formation

School engineer diploma or Master in CS

Outils

TensorFlow

C/C++

Python

Windows/Linux

Description du poste

InterDigital InterDigital is a global research and development company focused primarily on wireless, video, artificial intelligence (“AI”), and related technologies. We design and develop foundational technologies that enable connected, immersive experiences in a broad range of communications and entertainment products and services. Founded in 1972, InterDigital is listed on Nasdaq and is a registered trademark of InterDigital, Inc. More information is available at www.interdigital.com.

InterDigital R&I Center in Rennes, France, is looking for a PhD researcher in deep‑based video coding. The offer takes place in a research project focused on 2D video coding, deeply involved in standardization (MPEG, VCEG, JVET). The objective of the PhD thesis is to explore new coding algorithms based on deep‑learning solutions, focused on the improvement of inter‑prediction by using deep solutions to generate more accurate reference pictures. The main aim is to significantly improve coding efficiency compared to prior‑art solutions while addressing complexity issues.

Main Responsibilities

• Follow‑up the state‑of‑the‑art of published research and standardization in the field of Deep learning and Video Coding.
• Propose and implement new algorithms for video coding, in collaboration with the research team in the field of Video Coding and Deep Learning.
• Participate in the innovation effort through invention disclosures.
• Demonstrate and promote results in contributions to standards, peer‑review journals and conferences.

Profile

• School engineer diploma or master degree in computer science with experience in at least one of deep learning, machine learning, signal processing and/or related fields.
• Interest in Computer Vision and/or image processing and Deep/Machine Learning.
• Experience in software implementation: C/C++, Windows/Linux, Python, TensorFlow.
• Team spirit, enthusiastic, motivated, and creative attitude.
• Good communication skills and ability to present his activities internally and externally.
• Fluent English mandatory, French appreciated.

Location: Rennes, France

InterDigital is an equal employment opportunity employer. InterDigital will not engage in or tolerate unlawful discrimination with regard to any employment decision, policy or practice based on a person’s sex, gender, pregnancy (including childbirth, breastfeeding and related medical conditions), age, race, color, religion, creed, national origin, ancestry, citizenship, military status, veteran status, mental or physical disability, medical condition, genetic information, sexual orientation, gender identity or expression, or any other factor protected by applicable federal, state or local law. This policy applies to all terms and conditions of employment, including, but not limited to, recruiting, hiring, compensation, benefits, training, assignments, evaluations, coaching, promotion, discipline, discharge and layoff.