Join Us

We are recruiting postdocs, PhD students, master students, research assistants, and undergraduates. Research assistants and undergraduates can work with us on site or remotely.

What we do

We build edge AI systems: cloud-edge collaborative LLM serving, end-to-end acceleration of LLM applications, efficient generative AI, and container scheduling and resource management at the edge. See Research for details. Our work combines AI algorithms with system design and implementation.

What we offer

• Compute: Our research is supported by an interdisciplinary supercomputing center with 400 A100/A800 GPUs.
• A clear starting path: New students can follow our research starter handbook (in Chinese), from setting up the environment to reading and reproducing papers.
• Real research problems: Work on ongoing projects published at ICLR, ICML, ACM MM, IEEE TMC, IEEE TSC, and other venues, with open-source code.

Who we are looking for

• Interest in AI systems, edge computing, LLMs, or generative AI;
• Strong hands-on skills and the habit of solving problems independently;
• Steady time commitment and proactive communication.

Research directions

See Research. Current themes:

1. Cloud-edge collaborative LLM serving
2. End-to-end acceleration of LLM applications
3. Efficient generative AI
4. Edge container scheduling and resource management
5. Efficient multimodal inference and retrieval
6. Task scheduling and optimization in edge computing

Contact email is the address already listed on this site. Office location and meeting cadence are marked TODO for the lab to fill in.

How to apply

Email zhiqingtang@bnu.edu.cn with:

1. Your CV (courses and grades, projects, awards);
2. The research area you are interested in, and your thoughts on one related paper;
3. Links to any code or experiment reports, such as a GitHub repository.

Contact

• Email: zhiqingtang@bnu.edu.cn
• Address: Zhuhai, Guangdong, China
• PI homepage: Zhiqing Tang