Dynamic and time-dependent trip planning
As both historical and real-time data are available for more and more urban areas, integrating either one or the other in trip planning algorithms has received a wide interest in the literature in the past few years. Xerox Research Centre Europe (XRCE) has developed its own trip planner, which integrates both dynamic and time-dependent data. The Trip Planner team of the Data Intelligence group is pursuing research to improve models and algorithms, take into account additional data and enhance user personalization and experience.
The aim of the internship is to join the Trip Planner team for working on time-dependent dynamic shortest path problems. Models and algorithms will be proposed and tested in the context of the current solution.
As part of the 2nd year of your Master Degree, or final year of your Engineering School, you are looking for an internship lasting 5 or 6 months. Ideally, your diploma has a major in computer science and/or applied mathematics with some courses on operational research topics.
As prototypes are to be implemented, working knowledge of C++ is a plus and the candidate must be autonomous and motivated by optimization, innovation and research.
To submit an application, please send your CV and cover letter to both email@example.com and Vassilissa.Lehoux@xrce.xerox.com. Please specify "Internship:Dynamic and time-dependent trip planning" in your subject line.