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Publisher
source

CNRS

Just Landed

Postdoctoral Researcher in Image Coding and Enhancement CNRS in France

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

Deadline

Dec 1, 2026

Country flag

Country

France

University

CNRS

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Keywords

Computer Science
Electrical Engineering
Information Technology
Deep Learning
Computer Vision
Robotics
Object Detection
Multi-task Learning
Video Compression
Super-resolution
Embedded System

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About this position

This postdoctoral position is part of the EPERVIER project at CNRS and focuses on the development of new methods for image and video coding for both automatic analysis systems and human operators.

The successful candidate will work on machine-oriented compression: designing a coding solution that preserves the information most useful for artificial intelligence tasks such as object detection, classification, and localization of objects or people, while still enabling content reconstruction when human interpretation is needed.

The research will explore learned, adaptive and scalable coding architectures that can provide multiple levels of access from a single compressed representation. The aim is to organize the bitstream into successive layers, starting from a minimal representation for one or more machine tasks and extending to additional information that can improve other analysis tasks or support reconstruction for human viewing.

A major aspect of the project is the study of coding methods for embedded and drone-based transmission, where communication bandwidth, computational resources, energy consumption, and transmission conditions are constrained. The work is therefore positioned at the intersection of compression, computer vision, and efficient deployment on resource-limited platforms.

The position also examines how image enhancement methods can interact with coding when images are acquired in highly degraded conditions. In particular, the project will investigate whether restoration, denoising, and super-resolution can simultaneously improve compression efficiency and the performance of automatic vision tasks.

The recruited researcher will contribute to the study of learned compression for human and machine use, multi-task coding strategies, dynamic adaptation of coding to scene content and regions of interest, and objective functions balancing bitrate, perceptual distortion, and task performance.

Funding details

Available

What's required

No specific degree, GPA, language test, or other entry requirements are stated in the advert excerpt provided. The position seeks candidates able to study the state of the art in image and video coding, develop learned compression architectures, and work on computer-vision-oriented representations and enhancement methods.

How to apply

Apply through the official application page on Choisir le service public. Use the provided advert link to access the full listing and submit the required materials via the portal.

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