Academic

Data mining, Statistical Machine learning, Swarm robotics Project
(funded by JST and ANR, joint with Universite Paris-Sud, France)
www.i.kyushu-u.ac.jp/~suzuki/jstanr.htm

Starting date: April 1, 2009, or later.
Position will remain open until a suitable candidate is found.

Suzuki laboratory affiliated with Kyushu University seeks one full-time Post-Doctoral researcher in Data mining and Machine learning applied to Robotics.

The position, funded by the Japan Science Technology Agency (JST) on 12 months, is defined in the context of the Japanese-French collaboration on ``Integrating Symbolic Discovery with Numerical Machine Learning for Autonomous Swarm Control" (joint JST Kyushu University - CNRS Universite Paris-Sud). The project is scheduled from October 2008 to September 2011 but only at most one-year-basis employment is possible due to the regulations of Kyushu University. The salary is fixed after the regulations of Kyushu University and is comparable to that of an assistant professor.

Specifically, the candidate will do his or her research at the cross-section of statistical learning, robotics, and data mining of the logs of the robots. Candidates must have a strong background with good publications in several of the following fields: data mining, statistical machine learning, and robotics. He or she must be willing to become proficient in all of them.

The successful candidate will have a strong commitment to research and publication, and good communication skills in English. He or she will be available for possibly long visits to the French laboratory involved in the project. The ability to work as a part of an international research group, and participate into the production of deliverables to fixed deadlines is essential.

The location is in the Ito campus of the Kyushu University (40 minutes from Fukuoka downtown).

Candidates are welcome to send an e-mail with their CV (preferably as PDF attachment) to

• Einoshin Suzuki, suzuki@i.kyushu-u.ac.jp
• Michele Sebag, sebag@lri.fr
• Marc Schoenauer, marc.schoenauer@inria.fr