Job Description

The candidate will develop deep-learning frameworks and foundation models for transport phenomena across a wide range of spatial and temporal scales.

Qualifications

1. A Ph.D. degree in computer science, artificial intelligence, computer vision, or a closely related field.

2. Substantial research experience in deep learning on spatiotemporal predictive learning, particularly in generative model.

3. Experience in processing and fusing multimodal data.

4. Strong programming skills in Python and PyTorch, with experience in large-scale multi-GPU training on high-performance computing platforms.

5. A strong publication record, including first-author publications in top-tier AI conferences or leading peer-reviewed journals.