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Open nowPosted 33 days ago

【校招】人形具身基础模型研究员-物理智能中心

aicarrier/522799209 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【校招】人形具身基础模型研究员-物理智能中心aicarrier/522799 · Shanghai, Chinese Mainland

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  6. 57.8%60 days
This job: posted 33 days ago

The posting

岗位职责 面向人形机器人开展具身智能基础模型研究，围绕多模态感知、物理动态建模与动作生成，探索具备泛化能力的模型架构和训练方法。 开展世界模型研究，学习机器人、环境及交互过程的状态表示与动态规律，探索其在预测、规划和策略学习中的应用。 研发机器人运动控制模型，结合模仿学习、强化学习等方法，提升机器人在复杂任务中的运动能力、交互能力和鲁棒性。 开展具身模型端侧部署研究，探索模型压缩、知识蒸馏、量化及高效推理方法，优化受限算力下的推理延迟、资源占用与任务性能，并与工程团队协作完成真机验证。 跟踪前沿研究，形成可复现的算法实现、实验结论及高质量科研成果，推动研究方法在实际具身场景中的应用。

任职要求 计算机、人工智能、机器人、自动化、应用数学等相关专业博士，具备扎实的机器学习与深度学习基础。 在世界模型、强化学习、模仿学习、机器人运动控制或具身多模态模型中，至少一个方向具有深入研究经验。 理解机器人运动学、动力学与反馈控制基础，了解人形机器人的浮动基座、多关节耦合、平衡及接触约束，能够将本体特性纳入模型设计与实验分析。 熟练使用 Python、PyTorch 等工具，能够独立完成模型设计、训练调试、实验分析与算法实现。 具备严谨的科研思维，能够从实际问题中提出研究假设，设计有效的评测与消融实验。 具备良好的英文文献阅读、技术表达与团队协作能力，愿意参与从算法研究到机器人验证的完整研发过程。 加分项 具有机器人全身控制、灵巧操作、人机交互或多智能体学习相关研究经验。 熟悉 Isaac Lab、MuJoCo 等仿真平台，具有仿真到现实迁移或机器人实机实验经验。 具有大规模模型训练、分布式强化学习、模型蒸馏或推理优化经验。 在相关领域发表高质量论文，或拥有具有影响力的开源项目。

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