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Open nowPosted 43 days ago

科学基础模型科研实习生

sii-czxy/campus170 open roles

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Your applicationOpen now科学基础模型科研实习生sii-czxy/campus

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Share of postings closed within
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  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 43 days ago

The posting

1. 调研并整理蛋白质基础模型、长上下文建模、预训练、后训练及 AI for Science 等方向的前沿论文和技术资料，跟踪相关研究进展。 2. 复现典型蛋白质基础模型或相关开源方法，搭建实验环境并完成模型测试、性能对比和基础实验分析。 3. 参与蛋白质训练数据构建，包括数据清洗、预处理、数据配比设计和质量评估，协助建立高质量训练数据集。 4. 参与模型预训练、后训练、评测集构建及实验结果分析，探索提升蛋白质基础模型能力的方法。 5. 根据项目进展参与模型结构优化、训练策略改进、跨物种泛化及生物学任务适配等研究工作，整理实验记录、技术文档并进行阶段性研究汇报。

1. 招募对象：本科生、硕士研究生。 2. 计算机、人工智能、数学、生物信息学、生物学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，熟悉 PyTorch 等深度学习框架者优先。 4. 对以下方向具有研究兴趣：AI for Science；蛋白质基础模型；计算生物学；生物大模型；蛋白质结构与功能预测。 5. 能够阅读英文技术资料和科研论文，具备基础实验复现、数据分析和结果解读能力。 6. 能够使用 ChatGPT、Claude、GitHub Copilot、Cursor 等 AI 工具辅助文献调研、代码开发和科研分析者优先。 7. 有以下经历者优先：大模型训练与微调；论文复现；算法竞赛；生物信息学分析；蛋白质数据处理；开源项目开发。 8. 本科生重点考察编程基础、学习能力、研究兴趣以及利用 AI 工具辅助学习和科研的能力。 9. 硕士研究生希望具备一定的深度学习或科研项目经验，能够相对独立开展实验、分析结果，并利用 AI 工具提升文献调研、代码开发和实验迭代效率。 10. 实习安排：线上线下结合；周期3–6个月；每周投入20–30小时。

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