Posted 13 Oct 2026 (23 days ago) · Job 23927 · Read from the employer's SmartRecruiters board, last checked 5 Nov 2026, 08:48 UTC

Robotics Dynamics & Optimization Scientist_CR

Bosch · Shanghai, Shanghai, China

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Company Description

Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch.

 

Job Description

We are looking for a Robotics Dynamics & Optimization Engineer to develop optimization and control algorithms for robotic manipulators.
The role focuses on robot dynamics, constrained optimization, and optimization-based control. The engineer will formulate robot performance and motion requirements as optimization problems, and develop methods to improve robot configuration, dynamic capability, actuator utilization, and safe operation under physical constraints.
Key Responsibilities
Develop kinematic and dynamic models for robotic manipulators, including actuator, payload, and external force constraints.
Formulate robot motion and performance problems as constrained optimization problems.
Develop optimization algorithms for robot configuration, trajectory, joint load distribution, and dynamic performance.
Develop optimization-based control methods, such as Whole-Body Control, inverse dynamics control, QP-based control, or MPC.
Analyze robot capability under different payload, velocity, acceleration, and actuator constraints.
Develop constraint-handling methods to ensure safe operation near joint, torque, and actuator limits.
Implement and validate algorithms in simulation and on real robotic systems.

Qualifications

Master's degree or above in Robotics, Control, Mechanical Engineering, Automation, or related fields.
Strong knowledge of robot kinematics and rigid-body dynamics.
Strong background in constrained optimization and numerical optimization.
Experience with Whole-Body Control, trajectory optimization, MPC, inverse dynamics, or related optimization-based robotics methods.
Good understanding of joint torque, velocity, acceleration, payload, and actuator constraints.
Proficiency in C++ and/or Python, with experience using robotics or optimization libraries such as Pinocchio, CasADi, Drake, Crocoddyl, or equivalent tools.
Experience implementing and validating robot algorithms in simulation or on real robotic platforms.

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