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Open nowPosted 43 days ago

自主进化智能体科研实习生

sii-czxy/campus170 open roles

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This job: posted 43 days ago

The posting

1. 调研智能体自主进化相关技术：阅读并整理 Agent Harness、Agentic Reinforcement Learning、自进化智能体（Self-evolving Agent）等方向的前沿论文，理解智能体规划、执行、工具调用、反馈学习等核心机制。 2. 搭建与实验智能体系统框架：参与构建包含 Planner、Executor、Memory、Skill、Tools 等模块的智能体系统，在 Deep Research、Coding Agent 等复杂长程任务中开展实验与性能评估。 3. 研究智能体持续进化机制：探索如何利用智能体执行过程中的成功经验、失败轨迹和环境反馈，实现 Memory、Planning 和 Skill 模块的持续优化，使 Agent 能够自主提升任务完成能力。 4. 探索强化学习驱动的智能体学习方法：研究任务级、轨迹级和技能级奖励设计，以及信用分配机制，探索基于强化学习的 Agent 持续学习和能力增强方法。 5. 参与算法研究与科研成果产出：开展算法设计、实验验证和系统优化，探索从固定 Agent Harness 向能够根据经验自主进化的智能体系统转变的方法，并参与论文撰写及技术成果整理。

1. 招募对象：本科生、硕士研究生。 2. 计算机、人工智能、软件工程、数学等相关专业背景优先。 3. 熟悉 Python 编程，了解 Transformer、大语言模型（LLM）及基本 Agent 工作流程。 4. 了解强化学习基本概念，具备以下经验者优先：PPO、GRPO 等强化学习算法；Agentic RL（智能体强化学习）；LLM Agent 系统；Coding Agent 或开源 Agent 框架。 5. 具备较强的代码实现和实验分析能力，能够阅读英文论文并完成算法复现。 6. 本科生不强制要求强化学习科研经历，但希望具备扎实的数学基础、编程能力和快速学习能力；硕士研究生希望具备 Agent、LLM 或强化学习至少一个方向的研究基础。 7. 对“如何让智能体通过经验积累实现自主成长和持续进化”这一问题具有研究兴趣，能够稳定投入科研时间。 8. 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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