Job Description
The team lead for this project will work with researchers to investigate efficient methods for sensor data fusion, training new algorithms for improving state-of-the-art scene understanding and tracking for accurate navigation in complex scenarios.
Scene understanding will be investigated for shared control navigation with a novel personal mobility device developed specifically for close interaction with pedestrians and narrow spaces. Advanced scene understanding from onboard sensing should allow real-time evaluation of the environment for shared control with dynamic obstacle avoidance and planning.
Profile
* A highly motivated individual with outstanding experience in mechatronics systems and control.
* PhD degree from a university in Computer Science, Robotics, Mechanical Engineering, or related fields.
* Proven track record in robot navigation control or deep learning optimization for sensor fusion.
* Excellent English skills, with an interest in writing required.
* Adaptable and flexible to continuous changes associated with research demands.
* Strong robotics experience (ROS) for mobile systems, either in navigation, localization, or control.
* Confirmed publication on methodological areas of interest: mobile robots, multi-sensing fusion, time series modelling, or computer vision.
* Strong practical skills in field robotic systems.
* Strong experience with good coding practices in C/C++/C# and Python.
Workplace
We offer a full-time research position with a competitive salary in accordance with working, teaching, and research at ETH Zurich.
This is a unique opportunity to be at the forefront of cutting-edge research in AI embodied for robots, working with state-of-the-art technology and collaborating with some of the brightest minds in the field.
We value diversity and ensure a fair and open environment that allows everyone to grow and flourish.