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JD.com · 北京市-北京市

# 基于强化学习的医疗环境仿真探索

北京市-北京市 Internship or early career 

Listed on JD.com’s official careers site. Posted July 20, 2026. Check that it is still open and apply there.
[Apply on JD.com’s careers site →](https://campus.jd.com/#/details?id=8997)

[OpenNash Jobs](https://jobs.opennash.com/) / [JD.com](https://jobs.opennash.com/companies/jd/) / 基于强化学习的医疗环境仿真探索

## Job description

工作职责
- 负责设计并研发面向复杂医疗场景的强化学习底层仿真架构，解决高维度医疗环境中的状态空间建模难题。
- 构建与真实物理世界差距可控、具备高可信度的数字医疗孪生系统，支撑前沿医疗算法的闭环验证。
- 开发并调优医疗动态环境下的多智能体（Multi-Agent）协作算法，实现医疗资源调配与临床决策的最优规划。
- 结合海量脱敏临床数据，探索强化学习在医疗仿真验证中的创新应用，沉淀具备行业影响力的底层基建技术。 任职要求
- 计算机科学、人工智能、统计学或生物医学工程等相关领域的本硕博在校生。
- 具备深厚的强化学习理论功底，精通主流强化学习算法（如PPO、MADDPG等）及其在仿真环境中的应用。
- 具备卓越的代码实现能力与系统架构设计思维，能应对复杂仿真引擎底层的性能优化挑战。
- 对“AI+医疗”跨界技术充满技术信仰，具备优秀的逻辑分析与科研攻坚韧性。
- 在相关领域的高水平学术会议/期刊有论文发表，拥有重磅开源项目贡献或高水平算法竞赛获奖者优先。

## At a glance
- Posted by the employer: Jul 20, 2026
- First seen by OpenNash: Oct 19, 2026
- Last checked: Oct 19, 2026
- Listed for: 91 days
- Location: 北京市-北京市
- Employment type: Internship or early career[Apply on JD.com’s careers site →](https://campus.jd.com/#/details?id=8997)

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