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.
Skills Required
- PhD in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or a related field
- 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)
- 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
What We Do
Cygnify offers Talent Acquisition as a Service (TAaaS), providing a fully-managed team of experts, AI tools, and a candidate database on a flexible, month-to-month subscription model.
