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Open nowPosted 14 days ago

多模态医学基础模型科研实习生

sii-czxy/campus170 open roles

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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 14 days ago

The posting

1. 阅读医学影像、医学文本、多模态模型及医学人工智能相关论文，学习并整理领域前沿研究方法。 2. 复现指定医学多模态模型或开源方法，完成环境配置、模型运行和基础实验，熟悉模型训练、微调与评测流程。 3. 参与医学影像、文本及视频等多模态数据的预处理与跨模态对齐，构建支持模型训练与评测的数据流程。 4. 围绕医学多模态理解、复杂推理和自主学习等方向开展实验，比较不同模型结构、训练策略和数据配置对模型能力的影响。 5. 记录实验配置、模型结果和分析过程，维护可复现实验代码，并参与阶段性研究汇报。

1. 招募对象：本科生、硕士研究生。 2. 计算机、人工智能、数学、统计学、生物医学工程等相关专业背景优先。 3. 本科生：具备 Python 编程基础，掌握线性代数、概率统计等基础知识，了解机器学习基本概念，愿意学习 PyTorch 并完成模型复现和基础实验。 4. 硕士研究生：掌握机器学习与深度学习基础，能够使用 PyTorch 等框架进行模型调整和实验设计，具备阅读英文论文和分析实验结果的能力。 5. 对医学多模态人工智能、大模型、基础模型研究具有持续兴趣。 6. 不要求已有正式科研经历或论文发表；有模型复现、课程项目、算法竞赛或开源项目经历者优先。 7. 注重代码规范、实验可复现性和团队协作能力。 8. 实习安排：线上线下结合；实习周期：6个月以上；每周投入时间：20–30小时。

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