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Open nowPosted 43 days ago

时序智能与金融大模型科研实习生

sii-czxy/campus170 open roles

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Your applicationOpen now时序智能与金融大模型科研实习生sii-czxy/campus

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  6. 57.8%60 days
This job: posted 43 days ago

The posting

1. 调研时序智能与金融人工智能方向前沿研究：阅读并整理时间序列基础模型、金融预测、数值智能等方向的国内外论文，跟踪领域最新技术进展。 2. 探索时序基础模型在金融领域的应用：研究时序大模型（Time Series Foundation Model）在金融市场预测、风险分析、异常检测等任务中的应用方法，分析其相比传统模型的优势与局限。 3. 开展金融时序数据实验：参与金融时间序列数据的收集、处理与分析，完成数据清洗、特征构建、模型训练及实验评估。 4. 复现与优化相关算法模型：阅读前沿论文并复现经典方法，探索基于深度学习、Transformer、基础模型等技术的金融时序建模方案。 5. 进行实验分析与科研总结：设计实验方案，对模型预测效果、泛化能力和稳定性进行评估，整理实验结果并形成阶段性研究报告。 6. 参与科研项目推进：参加课题组讨论，汇报研究进展，根据项目需求参与数值基础大模型及金融智能应用方向的探索。

1. 招募对象：本科生、硕士研究生。 2. 计算机、人工智能、数学、统计学等相关专业背景优先。 3. 具备 Python 编程基础，能够完成数据处理、模型调用和实验分析。 4. 了解机器学习、深度学习基本方法，对时间序列分析、Transformer、基础模型等方向有兴趣。 5. 能够阅读英文技术资料或科研论文，具备一定文献调研能力。 6. 有科研项目、论文复现、算法竞赛、机器学习项目或开源项目经历者优先。 7. 具备良好的数学基础（概率统计、线性代数等），能够理解模型原理和实验设计。 8. 具备主动学习能力，能够针对开放问题开展探索，并完成阶段性科研任务。 9. 实习安排：线下科研实习；周期3–6个月；每周投入30小时以上。

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