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
- A Ph.D. degree in computer science, artificial intelligence, computer vision, or a closely related field.
- Substantial research experience in deep learning on spatiotemporal predictive learning, particularly in generative model.
- Experience in processing and fusing multimodal data.
- Strong programming skills in Python and PyTorch, with experience in large-scale multi-GPU training on high-performance computing platforms.
- A strong publication record, including first-author publications in top-tier AI conferences or leading peer-reviewed journals.