About the role
AI summarisedJoin our team to advance Embodied AI for robotics, focusing on Learning from Demonstration for contact-rich manipulation and intelligent skill acquisition. This role involves conducting applied R&D to develop, implement, and validate robot learning algorithms integrating motion, force/torque, and multimodal perception for real-world industrial applications.
ResearchOnsite
Key Responsibilities
- Design and execute experiments to collect, process, and analyse demonstration data for training intelligent robotic behaviours.
- Apply machine learning techniques, including deep-learning methods, to enhance robot control and decision-making processes.
- Translate research outcomes into functional prototypes and deployable robotics solutions for industrial applications.
- Contribute to the strategic development of Embodied AI and humanoid robotics capabilities.
- Leverage computer vision to improve robot perception and object recognition capabilities (if applicable).
- Continuously research and implement state-of-the-art algorithms and methodologies to improve robot performance and efficiency.
- Collaborate with cross-functional teams, including hardware engineers, software developers, and researchers.
- Support stakeholder engagement and technical discussions with industry partners.
Requirements
- PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
- Strong background in robot learning, Embodied AI, Learning from Demonstration, or related AI-driven robotics techniques.
- Proficiency in programming languages such as Python and C++.
- Hands-on experience with ROS2, simulation environments (e.g. Isaac Sim), and robotic hardware platforms.
- Knowledge of deep learning frameworks like TensorFlow and/or PyTorch.
- Strong communication skills to collaborate effectively with colleagues and present technical findings.