Senior Scientist - Robotics (Robotic Arm Manipulation)

About this role

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.