岗位职责 /Responsibilities:

1.基于控制逻辑与传感器数据，构建家电系统的图结构模型，描述变量之间的依赖与协同作用。

Use control logic and sensor data to model appliance systems as graphs,representing dependencies and interactions among variables.

2.研究并应用图神经网络方法，在仿真或实验数据上进行训练和验证，分析和预测多变量耦合对能效与性能的影响。

Apply graph neural network (GNN) methods to analyze, train and validate on simulation/experimental data, and predict the impact of variable interactions on efficiency and performance.

3.构建实验与数据分析框架，处理高维传感器数据与实验结果，提取图结构特征用于下游优化。

Build experimental and data analysis frameworks to process high-dimensional sensor data and extract graph representations for downstream optimization.

4.跟踪学术前沿并输出高质量研究成果，推动图神经网络在家电智能优化中的应用落地。

Monitor academic progress and publish high-quality research outputs to drive GNN applications in intelligent optimization of home appliances.

专业知识 /Skills and Knowledge:

1.具备跨学科思维，拥有计算机、人工智能、控制科学、数学或相关学科背景。

Strong interdisciplinary mindset w...