The Heudiasyc lab (CNRS – University of Technology of Compiègne) is offering a one year position starting February 1st, 2014 (few weeks later can be negotiable). Depending on his/her abilities and interests, the post-doctoral fellow will be involved in at least one of the following actions:
- Real-time perception for Intelligent road vehicles in dynamic urban environments by fusing multimodal sensing with prior knowledge (e.g. geo-referenced maps). This action includes SLAM with moving object detection and tracking, etc.
- Offline reasoning and scene understanding from sensing with uncertainty and contextual information. This action includes pixel-wise object class segmentation, learning of semantic models of the driving scene and human activities, such as categorization of simple behaviors, interaction patterns among dynamic objects or between the dynamic ones and infrastructure.
- Test-bed integration, experiments and evaluations. This action includes integration of core algorithms in a test-bed vehicle and evaluations on real-world data.
The post-doctoral fellow will be based in Heudiasyc laboratory in Compiègne (France – 1h north of Paris) and join the ASER or DI teams headed by Philippe Bonnifait and Yves Grandvalet. Heudiasyc is a joint laboratory with the Université de Technologie de Compiègne (UTC) and the French governmental agency for research (CNRS). In 2011, it was rated A+ (the highest rate) by the French Research evaluation agency (AERES). Heudiasyc fosters interdisciplinary research on information science and technology including machine learning, uncertain reasoning, operations research, robotics (including intelligent vehicles) and knowledge management. In 2011 Heudiasyc was awarded with an Excellence Lab (LabEx) from the Ministry, on the « Control of Technological Systems of Systems ».
The one-year fellowship is funded through an ANR/NSFC Sino-French project with Pekin University in China, and will start around February 1st, 2014 (~ 2500 euros per month, gross salary).
The candidate should have a PhD or equivalent in computer science or applied mathematics. The following qualities are desirable: strong interests in computer vision, machine learning, multi-sensor data fusion, target tracking or embedded systems; excellent record of academic and/or professional achievement; strong programming skills; good written and spoken communication skills in English.
Contact and application
Applicants should send (preferably as a single PDF file):
- a CV
- a brief statement of research interests
- references (with email and phone number)
- a sample of strongest publications
Contact: Franck DAVOINE and Vincent FREMONT