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Open nowPosted 44 days ago

化学反应基座模型与科研智能体研发实习生（AI算法方向）

sii-czxy/campus170 open roles

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Your applicationOpen now化学反应基座模型与科研智能体研发实习生（AI算法方向）sii-czxy/campus

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

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. 调研并整理分子基础模型、化学反应预测、科学智能体和 AI for Science 等方向的前沿论文与开源项目，跟踪领域最新研究进展，并形成阶段性技术总结。 2. 参与化学反应基座模型的研发与实验，包括分子表示学习、反应预测、自监督预训练任务设计、模型训练与性能评估等工作，完成数据划分、实验设计、消融分析和基准测试。 3. 参与科研智能体系统开发，为智能体搭建化学研究工具链，包括反应路径分析、文献解析、实验方案生成、模拟结果调用等功能模块，实现智能体在化学研究流程中的任务规划与工具调用。 4. 协助构建和优化化学反应及催化剂数据体系，包括数据清洗、结构标准化、质量控制以及实验结果回流数据管线搭建，为模型持续训练和优化提供支持。 5. 设计端到端实验评测流程，分析智能体在“提出研究假设—规划实验方案—模拟验证—结果反馈”过程中的能力表现，探索 AI 自主化学研究方法。 6. 参加项目组讨论并进行阶段性研究汇报，根据项目进展参与算法优化、系统迭代及科研成果整理。

1. 招募对象：本科生、硕士研究生。 2. 计算机、人工智能、数学、化学信息学、化学、材料科学等相关专业背景优先。 3. 具备 Python 编程基础，熟悉机器学习和深度学习基本方法，了解 PyTorch 等深度学习框架。 4. 了解分子机器学习、化学信息学或图神经网络相关方法者优先，熟悉 RDKit、ASE、DGL、PyG 等工具者优先。 5. 能够阅读英文技术论文和科研资料，具备基础实验设计、代码实现和结果分析能力。 6. 有以下经历者优先：大语言模型、分子基础模型或科学智能体相关项目经历；深度学习模型训练与复现实验经历；算法竞赛、开源项目或科研项目经历；化学反应预测、分子生成、催化剂设计等相关经验。 7. 本科生要求：具备机器学习基础和较强自主学习能力；不要求已有正式科研经历，更关注编程能力、学习能力和研究兴趣。 8. 硕士研究生要求：具备较完整的深度学习项目经验；能够相对独立开展模型实验、性能分析和技术调研工作。 9. 对 AI for Science、科研智能体和自主化学研究方向具有持续兴趣，能够稳定投入科研时间，并主动跟进实验进展。 10. 实习安排：远程科研实习；周期3–6个月；每周投入10–20小时。

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