Job Description

Conduct foundational and applied research in controlled generation for non-autoregressive and discrete diffusion language models. Specifically, focusing on overcoming key modeling barriers in diffusion large language models using techniques from tractable probabilistic models.

Qualifications

• A Bachelor’s Degree in Computer Science or related majors, with a dedicated focus on Machine Learning.
• A strong academic understanding of deep generative models, particularly diffusion models operating in discrete state-spaces.
• Proficiency in Python and deep learning frameworks (e.g., PyTorch), with hands-on academic or project about machine learning and generative AI.

More Information

Location: Kent Ridge Campus

Organization: School of Computing

Department : Department of Computer Science