Get Involved

We have internship positions at Peking University, jointly supervised by me and Prof. Liantao Ma. If you're self-motivated and interested in AI for healthcare, please don't hesitate to reach out with your resume. We are looking for intern students with interested in AI for healthcare, large language models and agent-based frameworks. We can offer PKU guaranteed Master / PhD admission for outstanding undergraduates/graduate students and recommendation letters.

Beyond mentoring, I'm happy to connect other collaborators. Please drop a mail to connect.

Project: DeepRHealth

Project Background:We are currently recruiting interns interested in medical AI and open-source projects to develop an R language medical data analysis toolkit. Our team's previously developed PyHealth open-source toolkit (1k+ stars on GitHub, 140,000 downloads) has become an important tool in the field of medical data analysis. The current project focuses on building the R language open-source ecosystem, aiming to provide efficient and user-friendly clinical data analysis tools for hundreds of thousands of R language medical researchers worldwide, promoting the intelligent transformation of medical research. We collaborate directly with the International R Language Foundation, committed to lowering the technical barriers for clinicians and medical researchers to use cutting-edge AI algorithms. Team members come from the University of Edinburgh, Peking University, and UIUC, focusing on tool development and algorithm research in the medical artificial intelligence field. The team leader is an international top expert and academician in the AI and medical fields.

Internship Content:Develop an open-source medical data analysis toolkit using R language, improving core functional modules Optimize existing AI algorithms (such as deep learning models) implemented in R language based on clinical needs Support tool documentation writing, user requirement research, and implementation of actual medical data analysis cases Participate in writing applied research papers based on project progress (opportunities for first author or co-first author)

What You Will Gain:

• Academic Resources: Guidance from PKU/UIUC/Edinburgh University mentors, participation in high-level paper publications
• Academic Advancement: Outstanding undergraduates/graduate students may obtain PKU guaranteed admission/direct PhD qualification or recommendation letters
• Career Development: Open-source project results will directly serve global clinical researchers, accumulating high-impact credentials
• Long-term Opportunities: Deep participation in algorithm innovation, co-publishing papers at top conferences

Currently, this internship emphasizes practical development with engineering goals as the priority, but still offers application-oriented paper output. Long-term collaborators have opportunities to delve into algorithm innovation and publish work at top-tier conferences.

Core Requirements:

• No limitations on major, grade, or location; proficient in R language and Python programming with solid code engineering capabilities
• Understanding of basic machine learning/deep learning theories and common algorithm frameworks (such as PyTorch/TensorFlow)
• Basic knowledge of mathematical statistics, data modeling, or medical informatics
• Self-motivated, able to commit 15+ hours per week, internship period of at least 3 months (long-term collaboration preferred)

Bonus Points:

• Experience contributing to open-source communities (GitHub projects, technical blogs, etc.)
• Medical or software engineering background, or familiarity with clinical data (e.g., electronic medical records, medical text)
• Mastery of cutting-edge algorithms such as Transformers, Graph Neural Networks (GNN), etc.

Please send an email if you are interested in the project.

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