This postdoc position (24 months) available immediately is proposed in the framework of the Audio Mobility 2030 (AM2030) project, which started in April 2023. AM2030 aims at enabling car manufacturers to have their own in-car audio application, regardless of the operating system. They will be able to deploy a global audio experience and offer the best content and proactive services to drivers. It is positioned as a true road companion that will help consumers adopt eco-responsible behaviors: vehicle self-diagnosis and maintenance reports, advice on driving and the use of on-board equipment.
The goal of this postdoc is to design a method to acquire a constraint model representing implicit information about the driver's (and passengers') preferences. The proposed method may be based on prior work on the topic of constraint acquisition .
We seek motivated candidates with a strong background in domains related to Machine Learning, Constraint Programming and/or Boolean Satisfiability. Good programming skills are also required.
 Christian Bessiere, Frédéric Koriche, Nadjib Lazaar, and Barry O’Sullivan.
Constraint acquisition. Artificial Intelligence, 244:315–342, 2017. Combining
Constraint Solving with Mining and Learning.