We have Postdoc positions available. The applicants are expected to have significant background in Computer Vision and/or Robotics and/or Machine Learning. Strong publications in top conferences and journals are required.
If interested, please send your CV together with the names of your referees to
Ivan Laptev.
The Willow team is extending its research to embodied computer vision and is interested in deploying its research on real robotic systems. The team has recently acquired a Tiago++ mobile two-handed platform (PAL Robotics) and an experimental platform with two UR-5 robot arms (Universal Robotics). The research of the team is focused on Deep Learning, Reinforcement Learning and advanced control of complex sensor-referenced robotic systems. Our ambition is to establish the theoretical and algorithmic foundations for robust control of robot movements directly from their sensor inputs for applications in dexterous manipulation and agile locomotion. To advance our research, WILLOW seeks engineering support for the maintenance and evolution (addition of new sensors, actuators or grippers) of its robotic platforms and the implementation of a common software framework to control real and simulated robot environments in a unified way. In the coming years, WILLOW also plans to acquire new robotic platforms (quadruped and biped robots, etc.).
The robotics engineer will be responsible for:
ensuring the maintenance and evolution of the team's robotic platforms and software;
establishing and maintaining a unified control architecture for all platforms, allowing a common interface to control the robots in both simulation and reality;
technically support the deployment of research on the robotic platforms, in close collaboration with the team's researchers and students. This implies setting up and maintaining technical documentation in English;
promote the team's software tools and results within the community;
provide demonstrations to visitors and at scientific events (science fair, science days).
We are lloking for candidates with
at least three years of experience
PhD or master degree in robotics (sensor referenced control, robot control scheme, motion planning, etc.);
strong experience in controlling complex robotic systems (manipulator arms, humanoid or quadruped robots);
strong experience in C++/Python, versioning (Git), virtualisation (Docker) and known integration;
strong experience with the ROS environment and classical software for controlling robotic systems (MoveIt, Gazebo, etc.);
experience in calibration and testing of robotic systems;
experience in the use of the ROS environment and classical software for controlling robotic systems;
experience in robot and sensor calibration;
thorough knowledge of mechatronics of robotic systems;
concrete experience in reinforcement learning and/or optimal control;
familiar with learning software (PyTorch, Tensorflow) and robotic simulators (Bullet, Mujoco, Gazebo);
concrete experience in reinforcement learning and/or optimal control;
good spoken and written English skills, ability to work in a team.
If interested, please contact and send your CV together with the names of two referees to
Ivan Laptev
and Justin Carpentier.