Senior Scientist - Robotic Arm Manipulation

We are partnering with a leading research and innovation organization 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 behaviors. • 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 • PhD in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or a related field. • Master's Degree in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering can be considered for Engineer role • 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. • 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. UEN:202329526G EA Licence: 23S2061