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Prospective Students
English | 中文
I will join Shanghai Jiao Tong University as an Associate Professor in July 2026, and am recruiting PhD students starting in 2027.
Research Directions
- AI for Drug Discovery. Predictive models of how biological systems respond to perturbations (single-cell transcriptomics, phenotypic bioactivity, molecular design), closing the loop between simulation, experiment, and clinical translation.
- AI for Medicine. Generalist medical foundation models, multimodal reasoning across imaging and clinical text, autonomous clinical decision support, and rigorous evaluation frameworks.
Who I Am Looking For
- Genuine curiosity about the intersection of AI and life sciences / medicine.
- Self-driven, clear thinking, and goal-oriented.
- Backgrounds in CS, EE, biomedical engineering, biology, or related fields are all welcome.
What You Will Get
- Hands-on mentorship on core research projects, from research direction to experimental details.
- The platform and compute resources of SJTU's School of AI to support high-quality work.
- Active academic collaborations with Harvard, Yale, Oxford, and other institutions abroad.
How to Apply
Email me at xiaomanzhang.zxm [at] gmail.com with the subject line "Prospective PhD 2027, [Your Name]", and include:
- CV (with GPA and ranking, if available)
- A brief statement (1 to 2 paragraphs) of your research interests
- Representative papers, projects, or code (links are fine)
- Transcripts (unofficial is fine)
我将于 2026年7月 加入上海交通大学人工智能学院担任副教授，2027年入学招收博士生。
研究方向
- AI for Drug Discovery。构建能够预测生物系统对扰动响应的AI模型（单细胞转录组预测、表型活性预测、分子设计）。长期目标是实现"模拟 → 实验 → 临床转化"的闭环，用计算的方式加速新药发现。
- AI for Medicine。构建通用医学基础模型，涵盖多模态推理（影像+临床文本）、自动化临床决策支持、以及医学AI的严格评估体系。
招生要求
- 对AI和生命科学/医学的交叉方向有真实的好奇心和热情，愿意投入时间。
- 自驱力强，逻辑清晰，目标明确。
- 欢迎计算机、电子、生物医学工程、生物学等相关背景的同学。
加入后你将获得
- 参与核心科研项目，我会提供持续深入的指导，从idea方向到实验细节。
- 上海交大AI学院的平台资源和充足的计算集群，全力支持你做出高质量的工作。
- 与哈佛、耶鲁、牛津等海外高校的学术合作网络，帮你拓展国际视野。
如何联系我
请发邮件至 xiaomanzhang.zxm [at] gmail.com，邮件标题写 "Prospective PhD 2027, [你的姓名]"，并附上：
- 个人简历（如有GPA与排名请注明）
- 一段简短的研究兴趣陈述（1 至 2 段）
- 代表性论文、项目或代码（链接即可）
- 成绩单（初次联系非官方版即可）
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