Faculty Position in Image Modeling and Understanding
il y a 3 semaines
Type of Structure: Telecom ParisTech, a leading CS/EE school of Université Paris-Saclay, is seeking an Associate Professor in the domain of image modeling and understanding.
Context and MissionThe group aims to develop its research activities at the crossroads of artificial intelligence and image understanding, with applications in the domain of health, particularly biomedical imaging. The association of symbolic and structural methods on the one hand (graphs, semantic networks, ontologies, spatial logics) and of numerical methods on the other hand (learning, image analysis, computer vision) is of prime importance, but still under-explored.
Required Skills- PhD or equivalent
- Outstanding academic record
- Strong knowledge, at both theoretical and applicative levels, in one or several of the following domains:
- Mathematical or computer science modeling for images
- Machine learning and artificial intelligence
- Biomedical imaging
- Experience in teaching if possible and pedagogical skills, ability to teach basic and advanced methods in machine learning, and applications in biomedical imaging
- Languages: English, French, or willing to learn French on the long term
- A post-doctoral or international experience, in an academic or industrial environment will be appreciated
- Team player, good social skills, able to develop international academic and industrial partnerships
- Ability to attract grants and funding at national and European levels
- Autonomous, self-motivated
The application file should be sent to the "service des Ressources Humaines" with copy to isabelle.bloch[at]telecom-paristech.fr and should contain:
- A detailed curriculum vitae
- A letter of motivation
- A document summarizing her/his experience in research and teaching, each of these activities being exposed with a thorough description of the different items
- His/her three major publications
- Names, addresses and electronic addresses of two highly qualified faculty members able to make recommendation on the applicant
- A research and teaching project (maximum length: 3 pages)
- If relevant, a link to a web page with additional information (demonstrations, courses, complete publications...)
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