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Open nowPosted 43 days ago

大语言模型知识蒸馏科研实习生

sii-czxy/campus170 open roles

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Your applicationOpen now大语言模型知识蒸馏科研实习生sii-czxy/campus

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The clock on this job

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

The posting

1. 阅读并整理大语言模型（LLM）、自然语言处理（NLP）、模型压缩与高效训练等方向的前沿论文，跟踪知识蒸馏领域最新研究进展。 2. 复现典型开源大模型及代表性研究方法，完成模型环境搭建、训练、推理和性能评测，建立规范化实验流程。 3. 参与大模型训练数据构建，包括数据收集、清洗、指令数据整理以及蒸馏数据设计，分析不同数据策略对模型性能的影响。 4. 围绕大语言模型知识蒸馏开展研究，探索教师模型与学生模型配置、蒸馏目标设计、训练策略优化等关键技术，提高模型压缩效率与性能保持能力。 5. 参与实验设计、结果分析、技术文档整理及课题组阶段汇报，协助完成研究报告和学术论文撰写。

1. 招募对象：硕士研究生。 2. 计算机科学、人工智能、软件工程、数据科学、数学等相关专业背景优先。 3. 具备机器学习、深度学习和自然语言处理基础，理解 Transformer、大语言模型（LLM）基本原理。 4. 熟悉知识蒸馏、模型压缩、高效微调等相关方法，了解教师模型—学生模型训练范式。 5. 具备 Python 编程能力，能够使用 PyTorch、Transformers 等深度学习工具完成模型训练、微调与评测，熟悉 Linux、Git 等基本开发环境。 6. 具备英文论文阅读、实验设计和结果分析能力，有大语言模型蒸馏、指令微调、模型评测或论文复现经历者优先。 7. 对大语言模型高效训练、知识蒸馏与模型部署方向具有持续研究兴趣，能够主动学习并开展科研探索。 8. 具备良好的科研执行能力和团队协作能力，能够稳定投入科研时间。 9. 实习安排：远程科研实习；周期3–6个月；每周投入30小时以上。

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