Senior Research Engineer II (Robot Learning & Manipulation)

We are seeking a Senior Research Engineer with a strong robotics learning background to lead research on visuomotor manipulation policies for humanoid robots, with an emphasis on advancing the state of the art while ensuring real-robot deployment.
Key Responsibilities:
Lead the research and development of learning-based visuomotor policies for humanoid robot manipulation, from problem formulation to real-world validation
Define research directions and technical roadmaps for manipulation capabilities such as grasping, object reorientation, bimanual manipulation, and assembly
Advance techniques including behavior cloning, reinforcement learning, and VLA-based reasoning, with a focus on novel contributions and publishable outcomes
Develop principled approaches to robustness challenges such as sensor noise, partial observability, contact dynamics, and environment variability
Oversee the research pipeline from data collection strategy and model training to evaluation methodology and deployment
Manage project milestones, deliverables, and timelines; coordinate with collaborators and stakeholders, and report progress to the PI
Supervise and mentor research associates, engineers, and PhD students working on the project
Collaborate with perception, controls, systems, and hardware teams to guide integration of learned policies into the full autonomy stack
Evaluate tradeoffs between learning-based and classical approaches and make principled architectural and design decisions
Lead the preparation of publications, technical reports, and grant/project documentation
Job Requirements
PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
Strong publication record in robot learning, manipulation, embodied AI, or related areas, demonstrated through publications in internationally recognised peer-reviewed conferences and journals (e.g., CoRL, RSS, ICRA, IROS, NeurIPS, CVPR, or equivalent venues).
Demonstrated experience developing and deploying robot learning systems on physical robotic platforms.
Demonstrated expertise in robot manipulation and visuomotor control.
Strong knowledge of behaviour cloning, reinforcement learning, imitation learning, or other learning-based manipulation methods.
Proficiency in Python and modern deep learning frameworks such as PyTorch or equivalent.
Proven ability to independently define research problems, design experiments, analyse results, and drive projects to completion.
Experience leading, supervising, or mentoring researchers, engineers, students, or project team members.
Strong communication and collaboration skills, with the ability to work effectively across multidisciplinary teams.
Preferred Qualifications
Experience working with humanoid or highly dexterous robotic platforms.
Experience translating research outcomes into deployed, operational, or commercial robotic systems.
Track record of successful collaboration with industry or research partners.
Demonstrated interest in advancing autonomous humanoid robotics through research and real-world deployment.
We regret that only shortlisted candidates will be notified.
Hiring Institution: NTU