Senior/ Scientist, Robotics (Robotic Arm Manipulation)

We are partnering with a leading research and innovation organisation to hire a Senior Scientist to advance next-generation robotics through Embodied AI and intelligent robot learning. This role focuses on developing advanced robotic capabilities, particularly Learning from Demonstration (LfD), contact-rich manipulation, and adaptive skill acquisition for real-world industrial applications. The successful candidate will contribute to applied R&D initiatives, bridging advanced research with practical deployment in manufacturing environments. Key Responsibilities: - Conduct applied R&D in Embodied AI for robotics, focusing on Learning from Demonstration (LfD) and contact-rich manipulation. - Design and execute experiments to collect and analyse demonstration data for intelligent robotic behaviours. - Develop and implement machine learning and deep learning algorithms for robot perception, manipulation, and decision-making. - Translate research outcomes into functional prototypes and deployable solutions. - Integrate multimodal perception, motion planning, and force/torque feedback into robotic systems. - Collaborate with cross-functional teams including robotics engineers, software developers, and researchers. - Engage with stakeholders and industry partners to support real-world deployment. Requirements - Hands-on experience working with robot arms or robotic manipulators. - Exposure to Learning from Demonstration (LfD), imitation learning, or robot learning techniques. - Practical experience working with real robotic hardware (not purely simulation or theoretical research). - Strong applied research mindset with ability to translate research into real-world solutions. - PhD in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or a related field. - Proficiency in Python and/or C++. - Experience with ROS/ROS2 and robotics simulation environments (e.g., Isaac Sim, Gazebo, Mujoco). - Knowledge of deep learning frameworks such as TensorFlow or PyTorch. - Exposure to industrial automation or manufacturing environments is advantageous. - Strong collaboration and communication skills.