Artificial Intelligence AimlMachine Learning

Qualification and Experience

Ph.D. degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, Mechatronics, or a closely related discipline. (Candidates who have submitted their doctoral thesis or are awaiting defense are also encouraged to apply)

Role & responsibilities

Technical Proficiency:

Strong theoretical and practical foundation in robotics systems, including:
Robot kinematics, dynamics, and control (serial and mobile robots)
Motion planning, trajectory generation, and real-time control o Sensor fusion and perception using multi-modal sensors (IMU, LiDAR, cameras, force/torque sensors, encoders)
Real-time systems, embedded controllers, and hardware software co-design for robotic platforms
Demonstrated hands-on experience with robotic hardware, including:
Mobile robots, manipulators, or humanoid platforms
Integration and calibration of sensors, actuators, motors, and control electronics
Development and debugging of low-level and high-level robotic software stacks
Exposure to Artificial Intelligence, Machine Learning, and Deep Learning with hands-on implementation, particularly for robotics applications, including:
Learning-based perception (vision, depth, SLAM, object detection, tracking)
Learning-based control, imitation learning, and reinforcement learning for robotic systems o Integration of AI/ML models into real-time robotic pipelines
Optimization, deployment, and benchmarking of AI models on robotic or edge platforms
Experience with robotic middleware and frameworks, such as:
ROS / ROS2, Gazebo, Isaac Sim, or equivalent simulation environments o Hardware abstraction, message passing, and distributed robotic systems
Proficiency in programming and system development using:
C/C++, Python, and scripting for robotics applications o Experience with simulation-to-real (Sim2Real) workflows is desirable
Exposure to edge computing and embedded AI platforms (e.g., Jetson Nano/Xavier, Raspberry Pi, ARM based SoCs) for deploying perception and control models on-board robots.
Knowledge of real-time constraints, safety considerations, and optimization techniques for robust autonomous robotic systems.
Ability to handle robotic datasets, including data collection, labeling, preprocessing, evaluation, and performance benchmarking
Commitment to rigorous and reproducible research, including structured experiments, open-source development practices, and systematic validation of robotic systems.
Proven ability to design, implement, integrate, and evaluate complete robotic systems, combining hardware, control, perception, and AI/ML components.

Research Excellence

Demonstrated publications in reputable journals and peer-reviewed conferences in robotics, AI, or related fields.
Strong written and oral communication skills for disseminating research results.
Ability to work collaboratively in interdisciplinary research teams involving robotics, AI, embedded systems, and control.
In addition to independent research, the postdoctoral researcher will mentor students, contribute to project supervision, and support collaborative research proposals and publications.
Role: Other
Industry Type: Education / Training
Department: Other
Employment Type: Full Time, Temporary/Contractual
Role Category: Other

Doctorate: Ph.D/Doctorate in Electrical, Mechanical