Postdoctoral Associate (Reflex and Habitual Motor Control for Embodied AI)
SINGAPORE-MIT ALLIANCE FOR RESEARCH AND TECHNOLOGY CENTRE
Singapore
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Phd in robotics or related field
Closed-loop control policy deployment
Deep learning and reinforcement learning
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The Singapore-MIT Alliance for Research and Technology (SMART) is seeking a Postdoctoral Associate to contribute to a research program focused on Embodied Artificial Intelligence, particularly in reflex and habitual motor control for robots. The role involves designing and implementing closed-loop control policies for robotic systems, with an emphasis on real-time action generation without continuous visual input.
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Job Summary
This position focuses on developing a new robotic foundation-model architecture that combines vision-language reasoning with high-frequency motor control grounded in force-torque and tactile feedback.
The successful candidate will design, train, and deploy closed-loop manipulation policies on physical hardware including industrial robot arms, quadrupeds, and humanoids.
The role involves working directly with partner institutions at A*STAR, NTU, and MIT CSAIL to publish in top-tier robotics venues and mentor graduate students.
Matching Summary
Match Score: 75
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The Singapore-MIT Alliance for Research and Technology (SMART) is seeking a Postdoctoral Associate to contribute to a research program focused on Embodied Artificial Intelligence, particularly in reflex and habitual motor control for robots. The role involves designing and implementing closed-loop control policies for robotic systems, with an emphasis on real-time action generation without continuous visual input.
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Skills & Requirements
Must-have
PhD in Robotics or related field
Closed-loop control policy deployment
Deep learning and reinforcement learning
Real-time robot middleware experience
Force-torque and tactile sensor integration
Nice-to-have
Sim-to-real transfer for contact-rich tasks
Experience with Vision-Language-Action models
Multimodal sensor fusion expertise
Collaboration across international institutions
GPU-parallel simulation knowledge
Key Requirements
Ph.D. in Robotics, Computer Science, Electrical Engineering, or Mechanical Engineering
Demonstrated experience deploying learned policies on physical robotic hardware
Strong publication record in top-tier robotics, learning, or AI venues