* Research novel methods for understanding the fundamental interplay between hardware and sensorial capabilities that are possible using current technology, and the needs of learning-based control methods for producing robust control policies for complex motor skills such as dexterous manipulation.

* Test the suitability of kinematic designs for robotic manipulators for specific dexterous tasks using motor learning in simulated environments.

* Contribute to the mechatronic design and prototyping of robotic manipulators that are deemed appropriate for specific tasks.

* Determine the relative importance of multiple sensing modalities (e.g. vision, touch, proprioception) for motor learning of complex manipulation tasks.

* Integrate full-stack robotic systems comprising hardware, control and learning.

* PhD in a robotics-related engineering field (Mechanical Engineering, Computer Science, Electrical Engineering, etc.)

* Extensive expertise integrating complex mechatronic systems comprising hardware, sensors, actuators, low-level firmware, control, communication, planning and learning.

* Expertise with intrinsic sensing modalities for manipulation, such as touch and proprioceptive sensing.

* Expertise with motor learning approaches, particularly focusing on the impact on hardware and sensorial capabilities.