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Open nowPosted 3 days agoWe saw it 36 min after it went up

强化学习研发实习生

wcn7iq2vq1am/86371181 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now强化学习研发实习生wcn7iq2vq1am/863711 · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

13.4% of postings close within 7 days. Measured by our own scanner across the market. wcn7iq2vq1am/863711 postings stay open a median of 12 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: posted 3 days ago

wcn7iq2vq1am/863711 median: 12 days open

The posting

【岗位介绍】 我们正在寻找对机器人与强化学习有强烈兴趣的研发实习生，参与机器人操作任务的强化学习与模仿学习算法研发。你将围绕仿真环境构建、算法研发与调优、Sim2Real 迁移等方向开展工作，与团队一起把算法推进到真实机器人系统上验证，解决机器人学习中的真实问题。

【工作职责】 1.仿真环境与训练系统建设 参与机器人操作任务的强化学习环境建模与仿真系统设计，构建高效、逼真的物理仿真环境。 2.强化学习与模仿学习算法研发 研发适用于机器人实际任务的强化学习与模仿学习算法，提升策略在真实场景中的泛化性、鲁棒性和样本效率。 3.算法改进与训练调优 针对机器人实际控制问题，改进和优化深度强化学习算法（如 PPO、SAC、TD3、TDMPC、RLPD 等），并结合模仿学习等方法提升训练效果。 4.Sim2Real 迁移 设计域随机化、系统辨识、自适应控制等方法，推动策略从仿真到真实的迁移，降低仿真与实际的差异。 5.实验分析与迭代 设计并执行训练与评测实验，分析实验结果、沉淀技术文档，与团队协作持续迭代算法与系统。

【任职要求】 1.在校学生，计算机、自动化、机器人、电子工程、人工智能等相关专业硕士及以上在读（特别优异的本科生也可以考虑），具备扎实的数学与算法基础。 2.熟悉常用强化学习算法（如 PPO、SAC、TD3、TDMPC、RLPD 等），具备算法实现或调优经验，熟练掌握 PyTorch、JAX 等至少一种深度学习框架。 3.具备机器人学基础，熟悉运动学、动力学建模，有实际机器人系统（机械臂、移动机器人等）算法开发或部署经验者优先。 4.具备良好的团队协作和沟通能力，对机器人技术有强烈兴趣和自驱力。

【加分项】 1.在强化学习、机器人相关顶会（NeurIPS、ICML、ICLR、RSS、CoRL 等）发表论文。 2.有强化学习真机部署经验。 3.有大规模并行仿真训练或仿真系统开发经验。

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