Weather AI Research Engineer: Physics-ML for Forecasting

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

The National University of Singapore is seeking full-time Research Fellows to develop hybrid physics-AI methods for weather applications. The role focuses on multimodal AI and foundation-model approaches using diverse data sources such as NWP outputs, satellite imagery, radar, and sensor networks.

You will build reproducible training pipelines, implement uncertainty quantification, and collaborate with weather-domain experts.

Qualifications

• PhD in Computer Science, Data Science, Engineering, Physics, or related.
• Strong Python and PyTorch; experience with multi-GPU/distributed training and performance optimization.
• Experience with real-world geospatial/sensor data (quality control, cleaning, visualization).
• Strong communication and collaboration skills.

Responsibilities

• Develop and benchmark multimodal AI / foundation-model approaches for spatiotemporal forecasting.
• Build reproducible AI training and evaluation pipelines, as well as uncertainty quantification strategies.
• Work at the intersection of physics and AI, with an emphasis on geospatial computational modelling.
• Collaborate with domain experts and operational stakeholders where relevant.
• Drive scientific breakthroughs and contribute to publications and cross-institutional collaborations.

Skills

Python

PyTorch

Multi-GPU training

Distributed training

Geospatial data handling

Communication skills

Education

PhD in Computer Science, Data Science, Engineering, Physics, or related

Job description

The National University of Singapore is seeking full-time Research Fellows to develop hybrid physics-AI methods for weather applications. The role focuses on multimodal AI and foundation-model approaches using diverse data sources such as NWP outputs, satellite imagery, radar, and sensor networks.

You will build reproducible training pipelines, implement uncertainty quantification, and collaborate with weather-domain experts.