The selected candidate will join the interdisciplinary team of the iCub project and will contribute to the implementation of perception and manipulation skills of humanoid robots.
We are looking for a talented and enthusiastic post-doctoral researcher who will join our team to study machine-learning algorithms to advance the capabilities of humanoid robots to interact with the environment, grasping and manipulating objects.
The focus is on strategies that allow autonomous learning, and incremental machine learning techniques for dynamically adapting to novel situations. Topics include:
* Perception of affordances;
* Scene segmentation;
* Robot self-perception for visual control of manipulation;
* Data-driven approaches to object grasping.
The ideal candidate will have a PhD in a relevant field (e.g. Robotics or Machine Learning) and the following skills:
* Proven experience working with real robotic systems;
* Knowledge of deep learning frameworks;
* Strong knowledge of programming languages, i.e. C/C++;
* Knowledge of robotic middleware like ROS and YARP.
The successful candidate will be offered a salary commensurate to experience and skills.
Please submit your application, including a detailed CV, and references, to [hidden email] quoting exactly ""BC 75221 - JP11 - Post Doc on Perception and Machine Learning for manipulation" in the e-mail subject.