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Open nowPosted 62 days ago

运控算法实习生

x2-robot/91213080 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now运控算法实习生x2-robot/912130 · Shenzhen, Guangdong, Chinese Mainland

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 62 days ago

The posting

1.参与全身强化学习与控制策略研发参与双足/人形机器人的全身控制策略研发，协助实现双腿、躯干、双臂及末端执行器的协调控制；探索 Imitation Learning、Offline / Online RL、Residual RL、Policy Distillation 等方法，提升运动控制策略的稳定性、泛化性与适应能力；参与构建支持行走、操作、人机协作、异常恢复等任务的通用控制策略。 2.参与 System 0 / System 1 分层控制与 Sensorimotor Intelligence 相关研发协助构建低频任务/技能策略与高频控制策略协同的分层控制架构；参与融合视觉、本体、力/触觉等多模态信息，建立感知—决策—动作—反馈闭环；探索力控、阻抗控制、接触模式切换及复杂人机交互等方向。 3.参与 Sim-to-Real 与 Robot Learning 研发闭环参与机器人仿真环境搭建、系统辨识、策略训练与 Sim-to-Real 能力建设；探索 Domain / Dynamics Randomization、Residual Policy、Teacher-Student 等方法；协助建立真机数据采集、失败案例挖掘、策略训练与持续迭代闭环。 4. 参与真机部署与系统优化参与控制策略在真实机器人上的实时部署、整机联调与实验验证；协助解决延迟、抖动、通信、执行器差异、策略切换等真实工程问题；参与搭建覆盖仿真、半实物和真机的策略评测与安全验证流程。

1. 毕业时间于2027 年 8 月及以后的国内外高校本科生、硕士生、博士生，计算机、机器人、自动化、控制、机械、电子等相关专业优先； 2.扎实掌握强化学习、机器人学、控制理论或机器学习中的一个或多个方向； 3.熟悉 Python / C++ / PyTorch，具备较强的算法实现与工程实践能力； 4.有真实机器人或机器人仿真项目经验，了解从算法研究、策略训练到实验验证的基本流程； 5.对具身智能、机器人学习、运动控制等方向有强烈兴趣，愿意深入真实机器人系统一线。

加分项 1. 有人形/双足机器人、机械臂、灵巧手、全身控制或复杂接触任务相关经验； 2. 有机器人强化学习、Sim-to-Real、大规模并行仿真经验； 3. 有 CoRL、RSS、ICRA、IROS、NeurIPS、ICML 等相关论文、竞赛或开源项目经验； 4. 对 Robot Foundation Model、VLA、World Model、Sensorimotor Intelligence 等方向有深入理解或持续关注； 5. 有较强的自驱力和问题拆解能力，能够在开放问题中持续探索和迭代。

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