Title:
Research Fellow on Data Fusion for Autonomous Driving

Duration: 12 months (renewable)

Program:

Advanced Driver Assistance Systems (ADAS) for autonomous vehicles make use many heterogeneous sensors such as radar, camera, LIDAR,  to perceive the surrounding environment. That is, awareness of the situation unfolding around the vehicle is simply not achievable by processing the data provided by a single sensor, but redundant views and multiple sensing modalities are required in order to build a comprehensive situational picture.

Data Fusion techniques aim at exploiting multiple data sources to obtain estimates that on average are better than the single sensor.

The goal of this research fellowship is to exploit data and information fusion techniques in order to assess the available drivable space for an autonomous vehicle.

The work will be performed on real data within a project involving a top car maker industry.

Qualifications:

• Master degree in Computer Science or equivalent. Ph.D. degree will be a plus.
• Knowledge of probability and belief functions theory. Knowledge of latest Machine Learning techniques will be a plus.
• MATLAB and C++ programming skills
• Publication record will be a plus

Starting date: ASAP

Please contact me if interested