职位描述：
1. 负责开发、部署和调试用于人形机器人灵巧手的先进操作算法，包含遥操作、力控、强化学习等领域。
Develop, deploy, and debug dexterous-hand manipulation algorithms for humanoid robots, including teleoperation, force/impedance control, and reinforcement learning.
2. 负责仿真环境的搭建与迁移，涵盖机器人运动学、动力学、传感器仿真、物理环境交互仿真等。
Build and transfer simulation environments: kinematics/dynamics, sensor simulation, physics interaction, and task environments.
3. 开发和改进先进的强化学习算法，实现机器人的操作任务。
Develop and iterate RL algorithms for complex manipulation tasks and drive real-world deployment.
4. 根据机器人在特定任务中存在的难点问题，参与针对具体技术难点的攻关。
Diagnose task bottlenecks and drive targeted problem-solving with cross-functional teams.
职位要求：
1. 自动化、计算机、人工智能、机器人等相关专业硕士及以上学历。
MS/PhD in Automation, CS, AI, Robotics, or related fields.
2. 熟悉机器人动力学、运动学、最优控制，有扎实的数学基础。
Strong fundamentals in kinematics, dynamics, optimal control, and math.
3. 精通Linux和Docker开发环境，熟悉C++和Python，掌握git工作流，具有良好的编程习惯。
Proficient in Linux & Docker; strong C++/Python; solid Git workflow and engineering practices.
4. 谦逊开放、思维活跃，具有团队合作意识。
Open-minded, collaborative, self-driven, and fast learner.
加分项 / Plus:
1. 熟悉主流强化学习、模仿学习等算法。
Hands-on with RL/IL (e.g., PPO/SAC/TD3/BC).
2. 熟悉Isaac Gym/Isaac Lab仿真，能够搭建复杂的仿真环境。
Experience with Isaac Gym/Isaac Lab and complex sim/training pipelines.
3. 灵巧手触觉/力传感应用经验；或 sim2real 实战经验。
Experience with tactile/force sensing or sim-to-real transfer.
4. 多关节机器人控制经验。
Experience controlling high-DoF robots.
5. 顶会/顶刊论文发表（CVPR/ICCV/ICRA/IROS/NeurIPS；IJRR/TRO/TPAMI 等）。
Publications in top venues (CVPR/ICCV/ICRA/IROS/NeurIPS; IJRR/TRO/TPAMI).
