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Open nowPosted 44 days ago

世界模型研究员（数据生成与增强）

wcn7iq2vq1am/86371186 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now世界模型研究员（数据生成与增强）wcn7iq2vq1am/863711 · 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. wcn7iq2vq1am/863711 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 44 days ago

wcn7iq2vq1am/863711 median: 1 days open

The posting

关于职位 您将负责世界模型驱动的机器人数据生成与增强：让世界模型从「训练与评测的对象」变成「生产数据的引擎」。工作包括应用或训练世界模型进行合成数据生成、设计数据增强框架与多样性度量，并验证合成数据对下游 policy 模型的真实增益。

核心职责： - 研究并落地世界模型驱动的数据增强框架：新颖视角合成、sim-to-real 风格迁移、轨迹条件视频生成，扩展和多样化真实世界机器人训练数据集。 - 构建数据多样性度量：基于视频聚类与去重的标准化多样性指数，用于采购与生成数据的配比决策。 - 评估合成数据价值：设计对照实验验证合成数据对下游 policy 性能的增益，与 VLA 评测线联动。 - 维护生成数据的管线与质量：与数据工程（2a）协作，保证生成数据可入训练管线、可追溯、可复现。

-计算机科学或相关领域硕士/博士（博士优先）； -在大规模视频模型、世界模型或数据增强方向有研究或工程经验（视频扩散模型、自回归视频模型、视频 Transformer 任一）； -精通 PyTorch，有分布式训练经验（FSDP、DeepSpeed、Megatron）； -对生成式建模与时间序列建模有扎实理解； -对数据质量与多样性有量化判断力（聚类、去重、分布度量、mixture 配比实验任一方向）。

加分项： -有将视频模型应用于机器人任务的经验（sim-to-real 迁移、合成数据生成、基于视频预测的规划或学习仿真器）； -具备机器人学习数据增强策略经验（轨迹增强、视图合成、领域随机化）； -熟悉真实世界机器人数据管道与遥操作数据格式； -在 NeurIPS、ICML、ICLR、CVPR 等顶级会议有第一作者发表记录； -熟悉 3D 感知视频生成、多视图合成或神经场景表示； -有把视频生成与具身 AI、强化学习或机器人操作连接起来的跨领域经验。

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