Job Description岗位职责:1、优化算法落地： 协助实施并迭代先验注入贝叶斯优化（Prior-injected Bayesian Optimization）机制，提升模型收敛效率。Optimization of algorithm implementation: Assist in the implementation and iterative implementation of the Prior-injected Bayesian Optimization mechanism, improve model convergence efficiency.2、闭环验证与分析： 协同团队在物理验证环境中开展闭环测试，整理实验数据并进行基线对比，量化验证系统效能。Closed-loop verification and analysis: The collaborative team conducts closed-loop testing in a physical verification environment, organizes experimental data, performs baseline comparisons, and quantifies the system performance.3、学术研究与支持： 协助进行文献综述与实验设计，使用 LaTeX 撰写高质量学术论文并制作数据可视化图表，支持顶会投稿。Academic research and support: Assist in literature reviews and experimental design, write high-quality academic papers using LaTeX and create data visualization charts, and support submissions to top conferences. 教育背景：数学、计算机科学、人工智能或相关专业的硕士或博士在读学生。一周出勤4-5天，能尽快到岗，可以实习6个月优先。 特定专业知识：1、具备贝叶斯优化或相关元启发式算法的实现经验。Experience in implementing Bayesian Optimization or related meta-heuristicalgorithms.2、具备良好的概率论、统计学基础及算法效能评估能力。Solid foundation in probability theory, statistics, and algorithm performanceevaluation.3、熟悉LaTeX学术写作,具备使用可视化工具进行科研成果展示的能力。Familiarity with LaTeX for technical writing and data visualization tools for scientificreporting.4、快速学习能力,能够迅速理解新领域知识与文献。Fast learner with the ability to quickly grasp new research domains and literature.5、出色的分析与问题解决能力,能够独立定义研究问题。Strong analytical and problem-solving skills, with the ability to define researchquestions independently.6、 熟练的英文技能7、其他技能：Python