Two Postdoc Positions: Vision group at Xerox Research Centre Europe

Xerox Research Centre Europe, based in Grenoble, France, is currently looking for two researchers with skills than can both integrate well and complement the current team; one focused on large-scale methods and the other on image analysis and feature extraction.

The Text and Visual Pattern Analysis Area (TVPA) group at Xerox Research Centre Europe, Grenoble, is a world-leading team that specializes in understanding, organizing, retrieving and enhancing both visual and hybrid content. Our research is the result of combining state of the art knowledge and skills from different fields such as machine learning, large-scale data mining, image analysis, and text retrieval. We have extensive experience and state of the art methods in image categorization, image enhancement, quality assessment and document image processing for both text and image content. Our main research lines currently focus on using this knowledge and expertise in the challenging areas of applied visual aesthetics and hybrid information access; going beyond the standard classification approach and developing techniques applicable in a variety of domains for assisted content creation and management.

Two candidates are sought with skills than can both integrate well and complement the current team; one focused on large-scale methods and the other on image analysis and feature extraction. This is an opportunity to join the group and research centre at a key time, and we are seeking researchers who will relish the challenge of not only carrying out leading research — through strong collaboration with Xerox researchers and also the wider academic community — but also influence the research agenda and potentially see strong deployment to be used worldwide in client systems.

For both positions, a strong background in machine learning and image or text processing is essential. Working with the team, the responsibilities will include inventing and developing novel techniques for document content analysis, both in terms of visual, text or hybrid media content. More specifically, there is currently a strong focus on large-scale learning and leveraging different types of media and social aspects to improve performance. The particular requirements for each position are detailed below:

Large-scale methods for retrieval and processing: the amount of digital content now stored and processed in a wide variety of application domains is every-increasing and the need for truly effective large scale techniques is clear. We are looking to develop retrieval and analysis methods that are computationally effective and can be used on image content, scanned forms, text-image hybrid data and even handwritten text. We are particularly seeking individuals with experience in one or more of large-scale methods, use of hybrid image/text data and handwriting recognition.

Image analysis and feature extraction: the team currently has state-of-the-art image processing techniques which have been repeatedly shown to be successful, through the strong publication record of the group, through excellent performance in competitions such as ImageCLEF and through deploying the technologies in various industrial applications. We are seeking a researcher with a blend of image analysis and machine learning skills that can use these technologies in different domains, and also develop the next generation of such methods. Experience with video analysis is desirable, as digital media of this type is increasingly common and is one of the focuses of Xerox customers for future digital asset management and real-time use of image processing technology.

Requirements (both positions):

* PhD in Computer Science in the area(s) of Machine Learning and/or Computer Vision

* Strong publication record and evidence of implementing systems

* Strong English-language written and oral communications skills

Informal enquiries are welcome and can be made in the first instance to the area manager: craig.saunders(at)

To submit an application, please send your CV and cover letter to both xrce-candidates(at) and craig.saunders(at)

About XRCE

More information about the position can be found at: