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Open nowPosted 44 days ago

科学智能体与强化学习科研实习生

sii-czxy/campus170 open roles

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Your applicationOpen now科学智能体与强化学习科研实习生sii-czxy/campus

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

The posting

1. 阅读并整理 AI4S、科学世界模型、模型驱动强化学习、科学智能体等方向的前沿论文和开源项目，跟踪相关研究进展。 2. 复现科学预测、快速仿真、强化学习及智能体相关代表性模型，搭建实验环境并完成训练、测试和基准对比分析。 3. 面向新能源、托卡马克、芯片设计、机器人等科学与工程场景，参与构建智能体交互环境、任务定义和评价指标体系。 4. 参与“方案生成—模型验证—策略优化—高保真校准”的实验流程设计，分析模型预测误差、计算成本和决策性能之间的关系。 5. 整理实验结果并参加课题组讨论和阶段性汇报，根据项目进展参与算法优化、开源系统建设和论文撰写。

1. 招募对象：本科生、硕士研究生。 2. 计算机、人工智能、自动化、数学、物理、能源、电子信息等相关专业背景优先。 3. 掌握 Python 编程基础，具备机器学习、深度学习或强化学习基础，能够使用 PyTorch 等框架完成模型训练和实验分析。 4. 对以下方向具有研究兴趣：AI4S（AI for Science）；科学智能体（Scientific Agent）；科学世界模型；模型驱动强化学习；智能决策与优化。 5. 能够阅读英文技术资料和科研论文，具备开源项目复现、实验设计、数据分析和问题定位能力。 6. 具备使用 ChatGPT、Claude 等大模型工具，以及 Claude Code、Codex 等 AI 编程或智能体工具的经验，能够将其7. 7. 用于文献调研、代码开发、实验分析和问题排查者优先。 8. 有以下经历者优先：科研项目；模型复现；算法竞赛；开源项目；新能源系统；托卡马克；芯片设计；机器人等相关研究或实践。 9. 具备一定的工程实践能力，能够参与模型训练、环境搭建、智能体开发和实验验证。 10. 对“如何利用 AI 智能体探索复杂科学与工程问题，实现自主设计、优化和决策”这一问题具有持续兴趣，能够主动推进研究任务。 11. 实习安排：线上线下结合；周期3–6个月；每周投入10–20小时。

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