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Open nowPosted 44 days ago

时序数据智能科研实习生

sii-czxy/campus170 open roles

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Your applicationOpen now时序数据智能科研实习生sii-czxy/campus

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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. 58.1%60 days
This job: posted 44 days ago

The posting

1. 调研时序基础模型前沿方向：阅读并整理时序基础模型（Time Series Foundation Model）、数值大模型、多模态数值学习等方向的前沿论文，跟踪领域最新研究进展。 2. 复现时序基础模型方法：阅读并复现代表性开源模型，搭建实验环境，完成模型运行、参数配置和基础性能验证。 3. 构建与处理时序数据集：参与多领域时序数据的清洗、整理、标准化和特征构建，为模型训练和评测提供数据支持。 4. 开展模型实验与分析：协助进行模型训练、实验设计和结果分析，评估模型在预测、异常检测等任务中的表现。 5. 参与科研协作与成果整理：参加课题组组会，汇报阶段性研究进展，整理实验记录、技术文档和研究报告。

1. 招募对象：本科生、硕士研究生。 2. 计算机、人工智能、数学、统计等相关专业背景优先。 3. 具备 Python 编程基础，了解机器学习、深度学习基本方法。 4. 能够阅读英文论文和技术资料，具备一定的科研调研和实验复现能力。 5. 有时序分析、深度学习、基础模型、算法竞赛、论文复现或开源项目经历者优先。 6. 具备数据处理、模型训练和实验分析能力，能够完成可复现的科研实验。 7. 对大模型、数值基础模型（Numerical Foundation Model）及 AI for Science 方向具有持续兴趣。 8. 具备主动学习能力，能够稳定投入科研时间，参与团队协作并完成阶段性任务。 9. 实习安排：线上线下结合；周期3–6个月；每周投入30小时以上。

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