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Open nowPosted 464 days ago

物理仿真算法工程师

x2-robot/index204 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now物理仿真算法工程师x2-robot/index · Shenzhen, Guangdong, Chinese Mainland

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Early applications get read.

11.9% 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. 4.4%3 days
  3. 11.9%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 464 days ago

The posting

岗位背景 当前团队在生成物理资产及用于 AI 训练的数据标注方面面临以下挑战： 物理参数（如摩擦力、关节驱动）采集耗时长 参数配置数量大，且专业要求高 产出效率低 相关人员需负责： 协助物理数据采集规范化及数据录入工作 针对 3D物理资产属性生成（尤其是刚体及软体部分）展开前沿方向研究 基于 3D 资产生成的特性需求，对现有物理引擎进行二次开发或功能优化 参与日常 Isaac 仿真环境维护、数据集引入及数据清洗工作 岗位要求 满足以下任意一条或多条： 具有良好的仿真功底，对现有物理引擎或自研物理引擎有过深度二次开发或独立开发经验 具备3D物理资产生成经验，参与过高质量物理资产生成项目（例如基于图片生成模型下的布料、软体、刚体物理属性等） 3年以上或同等经验及以上的游戏引擎开发工程师（可包含实习经历） 在Nips等平台发布过模拟属性生成相关文章的优先 熟悉物理参数（摩擦力、阻尼、弹簧系数等）采集与标注流程 能理解并优化物理仿真相关算法及数据 具有良好的论文功底 标准的代码工程开发能力 良好的沟通能力和团队协作能力 加分项 熟悉 Isaac Sim 或其他仿真平台 有自主完成物理资产生成或数据集构建的项目经验 对模拟有深度理解 对 3D 物理建模、AI 数据标注及仿真优化有浓厚兴趣 收获与成长 参与前沿 3D 物理资产生成与 AI 数据标注研究 接触物理引擎二次开发及优化 深入理解刚体、软体及复杂物理系统在仿真中的表现 有机会将研究成果应用到实际训练数据生成和工业仿真场景中

必要条件： - 教育背景： 计算机科学、物理学、数学、工程学或相关领域的硕士或博士学位。 - 编程能力： 精通C++，具备扎实的软件工程基础和大规模项目开发经验；同时熟练掌握Python，能够进行快速原型开发和脚本编写。 - 物理仿真经验： 深入理解刚体动力学、计算几何及数值分析等核心概念；拥有至少一款主流物理引擎的使用、二次开发或底层开发经验。 - 数学功底： 具备优秀的数学功底，尤其是在线性代数、微积分、数值方法和计算几何方面。 - 团队协作： 具备出色的沟通能力和团队合作精神，能够与来自不同背景的算法研究员和工程师高效协作。 加分项： - 有从零开始开发或主导开发物理仿真引擎的经验。 - 熟悉GPU并行计算，有大规模并行计算系统的优化经验。 - 在计算机图形学领域有深入研究，熟悉渲染管线、着色器开发等。 - 对机器人学有深入了解，熟悉运动学、动力学建模以及控制算法。 - 有机器学习或深度学习背景，了解强化学习并理解其对仿真环境的需求。 - 在顶级学术会议（如SIGGRAPH, NeurIPS, ICRA, ICLR等）上发表过相关领域论文者优先。

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