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Open nowPosted 74 days ago

校招-多模态感知算法工程师

nio/campus869 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now校招-多模态感知算法工程师nio/campus · Shanghai, Chinese Mainland
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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. nio/campus postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 74 days ago

nio/campus median: 1 days open

The posting

1、视触融合路面感知底层算法研发:深耕视觉、触觉融合的路面感知系统底层技术,搭建跨模态知识迁移算法框架,完成算法体系技术创新与突破;研究自监督感知学习方案,构建高性能自监督感知优化框架,持续提升复杂路面感知精度与鲁棒性。 2、多模态融合环境感知算法开发:研究声学、视觉、基础车载感知的多源信息融合算法,搭建统一、高效的舱内物理环境感知算法体系,实现全域、高精度、高可靠的车内环境感知能力。 3、负责感知算法建模、训练优化、仿真与实车验证,完成算法迭代与性能落地,输出核心技术专利、论文与技术方案,跟进行业前沿多模态感知技术,参与核心技术体系搭建与攻关。

一、核心硬性要求 1、学历背景:2027届应届博士,人工智能、计算机科学与技术、自动化、电子信息、机器学习等相关理工专业,深耕计算机视觉、多模态感知、深度学习方向;顶级成果硕士可破格遴选。 2、理论功底:具备扎实的博士层级深度学习、计算机视觉、多模态学习、特征融合理论基础,精通自监督学习、跨模态迁移学习核心原理,熟悉视觉、触觉、声学感知信号处理机制,具备底层算法创新与理论攻坚能力。 3、工程能力:具备完整的算法研发与落地能力,熟练使用Python、主流深度学习框架,精通模型训练、调优、特征设计、多源数据对齐与融合开发,能够独立完成底层算法框架搭建与性能迭代。 二、高阶优先条件 1、博士课题聚焦多模态融合、视触感知、计算机视觉、自监督学习、跨模态迁移学习相关方向,具备长期底层算法攻关经验; 2、拥有视触融合、声视觉融合、车载环境感知、自监督感知优化相关论文、专利、竞赛或项目成果者优先; 3、熟悉车载感知算法开发流程、多源传感器数据处理、模型部署与性能验证,具备独立技术创新、方案设计与成果转化能力优先。

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