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Open nowPosted 432 days ago

机器人Loco-Manipulation算法实习生

agirobot/internrecruitment367 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now机器人Loco-Manipulation算法实习生agirobot/internrecruitment · Shanghai, Chinese Mainland

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

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

  4. CV RocketApplied on agirobot/internrecruitment's own form.

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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. agirobot/internrecruitment postings stay open a median of 2 days.

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 432 days ago

agirobot/internrecruitment median: 2 days open

The posting

负责机器人 loco-manipulation 算法设计、开发与优化； 研究并实现基于强化学习（RL）、模仿学习（IL）等方法的行走与操作协同策略； 搭建仿真环境（如Isaac Gym、MuJoCo、Gazebo），开发和测试运动与操控任务； 跟踪领域前沿研究进展（例如VBC、AMP、Hover、FastTD3、TWIST等），将创新算法落地应用； 支持机器人在真实硬件上的算法部署、调试和性能优化。

机器人、计算机、自动化、人工智能等相关专业硕士及以上学历，博士优先； 扎实的运动控制、动力学、优化或强化学习理论基础； 熟练掌握至少一种主流物理仿真平台（Isaac Gym、MuJoCo、Gazebo等）； 精通Python或C++，具备良好的代码工程能力和调试能力； 有基于深度强化学习、模仿学习的机器人运动/操控策略开发经验； 具备良好的科研能力和英文文献阅读能力，能快速理解前沿工作； 实习时间6个月以上

加分项技能： 有真实机器人平台（如四足、双足或机械臂）上部署经验。 有分布式强化学习或大规模并行仿真训练经验； 熟悉全身控制（whole-body control）、接触动力学建模； 在顶级会议（ICRA、IROS、RSS、CoRL）或期刊上有相关发表记录。

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