Join Us

We are currently recruiting self-motivated Ph.D. students for Spring/Fall 2027 entry. We also welcome Research Assistants and Research Interns (on-site or remote) to join the Healthcare AI Lab at PolyU DSAI.

Our lab stands at the forefront of the Generative AI revolution in healthcare. We bridge the gap between fundamental AI innovation and clinical reality, aiming to develop Generalizable, Agentic, and Multimodal AI systems that can perceive, reason, and act in complex medical environments.

👉 Our latest work and publications are available on Google Scholar.

🔬 Research Pillars

• Medical Foundation Models
  Developing multimodal foundation models that integrate medical imaging, surgical video, electronic health records, and biomedical literature to support comprehensive clinical reasoning.
• Agentic AI for Healthcare
  Building clinical AI agents and intelligent copilots with capabilities in autonomous planning, multimodal reasoning, and video-language-action learning.
• Translational AI
  Moving beyond algorithm development to build deployable prototypes and conduct validation in real-world clinical settings.

🚀 Why Join Us?

• Frontline Research
  Work on emerging topics such as LLM agents, vision-language models, and world models with a supervisor who has first-hand expertise in building foundation models.
• Proven Mentorship
  Our philosophy is to help every student reach their full potential by providing training in independent research for future careers. Previous students under my mentorship have secured Ph.D. positions at leading universities, including Cambridge, Edinburgh, Nottingham, and UIUC.
• Clinical Resources
  Benefit from long-term collaborations with clinicians in USA, Hong Kong and Mainland hospitals, with access to high-quality medical data and expert feedback.
• Solid Support
  We provide ample GPU resources, international collaboration opportunities, and strong support and guidance for fellowship and scholarship applications.

🎯 Requirements

The following requirements primarily apply to Ph.D. applicants:

• B.S. or M.S. degree in CS, AI, DS, EE, BME, Math, Automation, or related fields.
• Solid math foundation, proficient in Python/PyTorch, and familiar with modern network architectures.
• Experience in CV, NLP, or Deep Learning. Prior work on LLMs, Agents, or Diffusion is a strong plus.
• A genuine passion for solving healthcare problems and resilience in tackling high-impact questions.

📝 How to Apply

Please email z.chen@polyu.edu.hk with the subject “Application for [Position] – [Your Name] – [Current University]”. Please merge the following materials into a single PDF:

• CV
  Include education, technical skills, research experience, and publications.
• Academic Transcripts
• Research Statement
  A brief statement of 1–2 pages of past work, future goals, and interest in our research directions.
• Representative Work (optional)
  Up to three papers or links to relevant GitHub projects.

💡 Notes

• Ph.D. Scholarships
  Scholarship opportunities include Hong Kong PhD Fellowship Scheme (HKPFS), PolyU Presidential PhD Fellowship Scheme (PPPFS), and PolyU Research Postgraduate Scholarship (PRPgS). Please visit the PolyU Fellowship and Scholarship Schemes for details.
• HKPFS Applicants
  Candidates with an outstanding academic record are encouraged to contact me before October.
• Undergraduate Research
  PolyU undergraduate students are welcome to join us through the Undergraduate Research and Innovation Scheme (URIS).
• Research Internships
  On-site and remote research internship will be considered based on the candidate’s availability, and alignment with ongoing projects.
• Response Policy
  Please be assured that I personally review every application with care. However, I will only be able to contact shortlisted candidates for interviews due to the high volume of inquiries. I genuinely appreciate your time and interest in our lab, and wish you the very best in your academic journey.

🌍 We are in an era where the next-generation AI will revolutionize healthcare. If you are passionate about building intelligent systems that can "think" like a clinician and "operate" like a surgeon, we invite you to join us!