Postdoctoral Research Position for Document Image Recognition & Understanding

Postdoctoral Research Position for Document Image Recognition & Understanding

The Computer Vision Center (CVC) is a non-profit research center established in 1995 by the Generalitat de Catalunya and the Universitat Autònoma de Barcelona (UAB). Its mission is to carry out cutting-edge research that has the highest international impact in the field of computer vision. It also promotes the transference of knowledge to industry and society.

Computer vision is an exciting research area and an omnipresent technology, essentially empowering machines with the sense of vision. The CVC is a successful marriage between knowledge and innovation. In addition to our cutting edge scientific achievements, we have established lasting ties with industrial partners and created several spin-off companies.

The Intelligent Reading Systems (IRS) group counts with more than 20 years of research and technology transfer experience in computer vision systems for extracting and interpreting written (textual or symbolic) information in images. The group is an international leader in scene text understanding, document image analysis, graphics recognition, handwritten recognition, musical scores understanding, and human-document interaction. It is a recognized consolidated group of the Catalan research systems since 2005. With more than 30 members, the group is one of the biggest ones worldwide in its field. The members of the group have produced more than 300 scientific publications and have participated in a large number of European and national research projects, as well as numerous technology transfer activities.


The IRS research group seeks applications to fill a postdoctoral applied research position focused on the development of document analysis algorithms applied to identity documents such as passports, national id cards, driving licenses, etc. to detect documents digitally modified. The final goal of this position is to research in an application field in which data is scarcely annotated and the number of samples per class, unbalanced. Experiments will be carried both on large scale public datasets as well as in-house private datasets coming from industrial partners.

The successful candidate will work in a research environment but attached to the funded EU project SOTERIA[1]. This project will combine a digital identity secured by a high-level identification with a decentralized data storage platform. The SOTERIA platform will be user-centric, accessible to everyone, without the need for specific ICT skills. It will protect the privacy of the European citizens and give them the full control of their data, ensuring that only the data that is needed to access to a service is shared with the service provider. It will also include an educational tool to raise the awareness of citizens on these issues.

[1] This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 101018342.

Main duties

  • Design and develop novel document forensics algorithms to detect documents digitally modified,
  • Research on few-shot and/or semi-supervised models trained with scarcely annotated datasets,
  • periodically reporting of the different project advances with SOTERIA partners.


  • PhD in computer science specialized in machine learning and, in particular, document image analysis,
  • good publication record,
  • strong programming skills in Python and/or C++,
  • knowledge and demonstrable experience with Deep Learning frameworks (Tensorflow, Pytorch, …) and image analysis packages (OpenCV, PIL),
  • experience working in Linux computing environments,
  • experience in machine learning, GPU programming, distributed data processing systems or high performance computing will be a plus,
  • able to work independently as well as within an interdisciplinary team,
  • fluent in English. Good communication skills.

Type of contract

  • 1 year of PostDoctoral contract, salary according to the CVC labor categories

Application process

  • Motivation letter
  • 2 Reference letters

If interested, please send your CV, motivation and reference letters through this website, indicating offer code 27072021_POSTDOC-SOT

Application deadline: September 30th 2021

CVC’s Open, Transparent and Merit-based (OTM-R) Recruitment process

The CVC’s approach to recruitment is based on a transparent merit-based approach. Job offers are publicly posted in our web site and for the suitable positions they can also be found in the CVC Euraxess web profile . The general guidelines are stated in the CVC-OTM-R Recruitment Process document

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