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Open nowPosted 33 days ago

【校招】智能文档理解青年研究员-数据平台中心

aicarrier/522799209 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【校招】智能文档理解青年研究员-数据平台中心aicarrier/522799 · Shanghai, Chinese Mainland

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

The posting

1. 负责多模态与智能文档理解关键技术研究，面向科学文献、技术报告等复杂文档，提升文本、图像、表格、公式等内容的识别、结构化与语义理解能力。 2. 研究文档结构建模、图文语义对齐与跨页信息关联等方法，实现从元素解析到内容理解的能力提升，支撑高质量训练语料构建与科学信息检索。 3. 建设训练数据与评测体系，研究数据合成、质量筛选及自动化评估方法，系统评估解析准确性、结构完整性、语义一致性与下游应用效果。 4. 开展多模态模型训练、适配与推理优化，与工程团队协作推动研究成果在大规模文档处理中的落地，兼顾效果、效率与稳定性。 5. 独立牵引方向内的研发项目，承担技术路线设计、关键问题攻关与交付推进，指导工程师及合作学生，参与骨干培养与团队建设。

1. 计算机、人工智能、模式识别等相关专业，博士及以上学历。 2. 在文档智能、多模态大模型、计算机视觉或自然语言处理等至少一个方向具有深入研究或实践经验，并有可展示的成果。 3. 具备扎实的 Python 编程能力，熟悉 PyTorch 等深度学习框架，能够独立完成数据构建、模型训练、实验验证及关键模块开发。 4. 具备较强的问题定义、实验设计与误差分析能力，能够定位数据、模型及处理流程中的瓶颈，通过系统实验验证改进效果。 5. 具备独立负责科研或研发项目的能力，能够结合实际需求判断技术优先级，组织协作并推动成果落地，愿意承担技术指导与团队协作职责。

加分项： 1. 有复杂版面、表格、公式、科学图表或长文档理解经验，熟悉科学文献等专业文档的处理难点。 2. 有多模态模型微调、强化学习、合成数据或跨模态对齐经验，或参与过大规模文档解析与数据生产系统建设。 3. 有高质量论文、开源项目或实际应用成果；有带领小团队、指导学生或组织跨团队合作的经验。

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