Job Description

We are looking for a highly motivated and accomplished Research Scientist with expertise in Embodied AI and robotics to join our cutting-edge team. In this role, you will play a key part in developing and deploying advanced robotic applications, with a focus on robot motion control, multi-modal fusion and machine learning for complex manipulation and mobility tasks.

Roles & Responsibilities

• Conduct fundamental and applied research in embodied AI, focusing on perception-action loops, multi-modal learning, and real-time decisionmaking.
• Develop and implement learning-based methods (e.g., reinforcement learning, imitation learning, foundation models) for complex manipulation, navigation, and interaction tasks.
• Design experiments to evaluate intelligent behaviors in both simulation and real-world scenarios using physical robotic platforms.
• Lead the integration of AI models with low-level control systems to enable adaptive, autonomous, and robust robot behavior.
• Collaborate closely with engineers and other scientists to translate research breakthroughs into deployable software systems.
• Engage in long-term planning of research direction in embodied AI aligned with organizational goals and technological trends.
• Provide technical mentorship and foster a collaborative, research-driven culture within the team.
• Maintain high standards of software engineering, experimentation, and documentation.

Job Requirements

• Ph.D. in Robotics, Computer Science, Electrical Engineering, or a related field.
• At least 2 years of experience
• Experience in machine learning, sensor fusion, hardware/software integration, with a strong portfolio of relevant projects.
• Deep understanding of robot perception, control, and learning, with an emphasis on closed-loop intelligent behaviors.
• Experience with embodied agents in simulation and/or physical robot platforms, humanoid systems is a plus.
• Strong programming skills in C++, Python, or similar languages commonly used in robotics.
• Experience in software development, including version control and continuous integration techniques.
• Knowledge of deep learning frameworks for building and training deep learning models.
• Experience in ROS has a good advantage
• Strong commitment to solving technical challenges, approaching obstacles with a positive and determined mindset.
• Strong communication skills to collaborate effectively with colleagues and present technical findings.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.