Digital Twin Research Engineer (Meteorological Forecasting and Disaster Response)

Digital Twin Research Engineer (Meteorological Forecasting and Disaster Response)

Core responsibilities

1. Platform development and integration

◦ Based on Cesium or Unreal Engine 4/5, develop a three-dimensional visualization module for a meteorological disaster warning system, realizing data-driven dynamic scene rendering (such as typhoon paths, rainfall cloud maps, landslides, and internal flooding analysis).

◦ Integrate multi-source data (satellite, radar, ground monitoring stations, IoT sensors), and achieve real-time synchronization between physical entities and virtual models through API or protocols (such as MQTT, WebSocket).

◦ Optimize engine performance, solve technical difficulties such as large-scale terrain rendering, particle effects (such as wind field simulation), and data loading delays.

2. Algorithm and model development

◦ Combine meteorological, hydrological, and geological disaster models with AI algorithms to develop disaster prediction and simulation functions (such as landslides and internal flooding caused by heavy rain, disaster situation simulation).

◦ Design lightweight data compression and transmission schemes to support efficient handling of massive spatio-temporal data.

3. Cross-team collaboration and delivery



◦ Write technical documentation, including system architecture design, interface specifications, user manuals.

Job Requirements

Essential conditions

1. Technical background

◦ Proficient in any of the following technology stacks:

Cesium direction: Proficient in JavaScript/TypeScript, familiar with Cesium engine architecture, GIS data processing (such as oblique photography, BIM, point cloud), and three-dimensional Web system performance optimization experience.

Unreal Engine direction: Proficient in C++, familiar with UE blueprint system, rendering pipeline, physical simulation (such as fluids, particle effects), and UE4/UE5 project development experience.

◦ Familiar with common data communication protocols (TCP/UDP/HTTP/WebSocket) and databases (MySQL/MongoDB).

2. Experience and education

◦ Bachelor's degree or above, majoring in Computer Science, Geographic Information Systems, Meteorology, etc.;



3. Soft skills

◦ Have strong logical thinking and cross-team communication skills, be able to quickly understand business pain points and design technical solutions.



• Familiar with meteorological data formats (GRIB/NetCDF);

• Master Python scientific computing library (NumPy/Pandas), with experience in developing time series prediction algorithms;

• Have experience in integrating UE and Cesium (e.g., through plugins to achieve engine interoperability);

• Understand edge computing, cloud-native (Docker/K8s) deployment solutions.