1. Develop and optimize humanoid robot simulation environments using engines such as Isaac Lab, NVIDIA PhysX, and Newton Dynamics, supporting R&D for perception, control, and motion planning modules. 2. Design and implement high-fidelity physical modeling, including rigid bodies, soft bodies, contact mechanics, and sensor simulation, providing precise simulation conditions for algorithm validation. 3. Integrated and debugged algorithms for robot control, reinforcement learning, and motion generation to construct a repeatable, scalable simulation testing framework. 4. Continuously optimized simulation performance and stability to accelerate algorithm iteration cycles while supporting simulation-to-real (Sim2Real) migration with physical robot systems. 1. 基於 Isaac Lab、NVIDIA PhysX、Newton Dynamics 等引擎搭建和優化人形機器人仿真環境，支持感知、控制及運動規劃等模組研發。 2. 設計並實現高保真物理建模，包括剛體、柔體、接觸力學、感測器仿真等，為演算法驗證提供精確模擬條件。 3. 集成並調試機器人控制、強化學習、運動生成等演算法，構建可重複、可擴展的仿真測試框架。 4. 持續優化仿真性能和穩定性，縮短演算法迭代週期，並支持與真實機器人系統的仿真-實物遷移（Sim2Real）工作。

1. Master the theoretical foundations and algorithms of artificial intelligence, pattern recognition, and deep learning 2. Understand Isaac simulation-related technologies and 3DGS reconstruction techniques; candidates with practical robotics project experience or competition experience are preferred 3. Proficient in C/C++ and Python programming, familiar with Linux and ROS systems 4. Possess strong teamwork and communication skills, along with excellent learning capabilities 1. 掌握人工智慧、模式識別、深度學習理論基礎和演算法 2. 瞭解Isaac仿真相關技術，瞭解3DGS重建技術，有機器人專案實際經驗或比賽經驗者優先 3. 熟悉C/C++和Python編程，熟悉Linux系統和ROS系統 4. 具備良好的團隊協作能力和溝通能力，具備良好的學習能力