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Open nowPosted 44 days ago

神经网络与储备池计算科研实习生

sii-czxy/campus170 open roles

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Your applicationOpen now神经网络与储备池计算科研实习生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. 阅读并整理循环神经网络、储备池计算、神经动力学及神经形态计算等方向的相关论文。 2. 构建和训练小型循环神经网络、储备池网络等神经网络模型，研究神经元之间的局部连接如何形成记忆、计算与动态响应能力。 3. 比较分析神经元集群与机器人、车流、鸟群、蚁群等物理群体在信息处理和时序计算中的共同机制。 4. 开展记忆能力、时序预测、动态系统建模或机器人控制等实验，分析网络规模、连接方式和动力学特性对性能的影响。 5. 探索如何将神经网络中的计算机制迁移到机器人集群，或利用真实物理群体形成新的神经形态/物理计算方法。

1. 高中生、本科生、硕士研究生。 2. 高中生：不要求正式科研经历，具备数学、物理、编程、机器人基础和兴趣即可，有竞赛经验为佳。 3. 本科生与硕士生：计算机、人工智能、数学、物理、自动化、控制科学、电子信息等相关专业背景优先。 4. 具备线性代数、微积分、概率统计等基础，了解机器学习或神经网络基本原理。 5. 具备 Python 编程能力，能够使用 PyTorch、NumPy 等工具完成模型训练、数据分析和实验。 6. 对循环神经网络、储备池计算、动力系统、神经形态计算中的至少一个方向有一定了解者优先。 7. 有深度学习项目、论文复现、科研训练、数学建模或算法竞赛经历者优先。 8. 能够阅读英文论文，对“神经元为什么能够通过简单连接形成复杂计算能力”这一类基础问题具有兴趣。 9. 线上线下结合，实习周期3–6个月，每周预计投入20-30小时。

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