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Open nowPosted 44 days ago

具身模型推理优化科研实习生

sii-czxy/campus170 open roles

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Share of postings closed within
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  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 44 days ago

The posting

1. 具身智能与端侧模型调研：阅读并整理端侧大模型、具身智能、模型压缩、推理优化以及 AI 芯片架构等方向的前沿论文与技术资料，跟踪相关研究进展。 2. 具身模型复现与部署实验：复现并测试主流开源具身模型（如 Pi0.5 等），完成模型微调、推理部署和基础性能评估，分析模型在不同计算环境下的运行表现。 3. 模型压缩与推理优化研究：参与模型量化、压缩、编译优化和推理调度等实验，分析模型在端侧设备上的延迟、显存占用、功耗和吞吐性能等指标，探索高效部署方案。 4. 视觉—语言—动作模型实验研究：参与视觉—语言—动作（VLA）模型的数据处理、轨迹数据分析、仿真 rollout、机器人任务测试及多任务泛化验证，支持具身智能模型能力提升。 5. 软硬件协同优化探索：结合端侧智能计算需求，探索模型、编译框架与 AI 芯片之间的协同优化方法，完成实验记录、性能分析和技术文档整理。

1. 招募对象：本科生、硕士研究生。 2. 专业背景要求：计算机科学、人工智能、软件工程、电子信息、集成电路、自动化、微电子等相关专业优先。 3. 知识基础要求：了解机器学习、深度学习、计算机体系结构、操作系统或编译原理中的一项或多项；对具身智能、机器人、模型压缩或 AI 芯片方向具有研究兴趣。 4. 编程与实验能力：具备 Python 编程基础，能够使用 Linux 环境和常见深度学习框架完成模型实验；具备 C/C++、CUDA、编译器或硬件描述语言基础者优先。 5. 科研能力要求：不要求已有正式科研经历，更关注学习能力、工程实践能力以及对端侧智能计算方向的持续研究兴趣。 6. 实验分析能力：能够阅读英文论文和技术文档，具备实验记录、性能分析、问题定位和结果总结能力。 7. 综合能力要求：能够稳定投入科研实习时间，持续参与模型实验、端侧部署及软硬件协同优化工作，并具备良好的团队协作能力。 8. 对以下方向具有研究兴趣：具身智能模型（VLA）；端侧大模型部署；模型压缩与量化；推理优化；AI 芯片与软硬件协同设计。 9. 实习安排：线下科研实习；周期6个月以上；每周投入30小时以上。

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