Current Vacancies

Postdoctoral Researcher/Assistant Professor (Multimodal Medical Large Models)

博士后/助理研究员（多模态医学大模型方向）

Job Responsibilities

1. Design pretraining frameworks for multimodal medical data (text/EMRs, images, temporal physiological signals).

2. Develop cross-modal alignment techniques using medical knowledge graphs for interpretable diagnostic reasoning.

3. Create trustworthy AI systems for complex medical decision-making.

4. Publish in top venues (CVPR, NeurIPS, ICLR, TPAMI, etc.) and secure patents.

5. Support grant proposals and technology transfer initiatives.

Requirements

1. PhD in AI, NLP, Clinical Informatics, or related disciplines.

2. Hands-on experience with multimodal LLMs (CLIP, BLIP, LLaVA, InternVL, QwenVL, DeepSeek-R1, etc.).

3. Expertise in PyTorch/TensorFlow and multimodal fusion architectures.

4. Track record of high-impact publications.

5. Healthcare domain experience preferred.

Application Method

Please submit CV, representative publications (highlighting 1-2 first-author papers) to hr02@cair-cas.org.hk. The subject of the email should be marked as Application for [Postdoctoral Researcher/Assistant Professor (Multimodal Medical Large Models)]-[Name].

岗位职责

1. 研发融合医学文本（电子病历）、影像、时序生理信号等多模态医学数据的预训练框架。

2. 探索基于医学知识图谱的跨模态对齐技术，开发面向多模态、可信、可解释的复杂医学推理诊断技术。

3. 发表高水平研究论文（包括CVPR、ICCV、NeurIPS、ICLR、TPAMI、TMI、MedIA 等），申请国家发明专利。

4. 协助科研项目申请工作。

5. 协助研究成果的落地转化工作。

职位要求

1. 博士学位，人工智能、自然语言处理、临床医学信息学等相关方向。

2. 熟悉多模态大模型（如 CLIP、BLIP、LLaVA、InternVL、QwenVL、DeepSeek-R1 等）的开发与应用。

3. 熟练掌握C/C++、PyTorch/TensorFlow框架。

4. 具备较强的科研能力，有顶级会议或期刊论文发表经历。

5. 有医疗场景研究经验者优先。

申请方式

请将个人简历、代表性出版物（1-2篇第一作者论文）发送至hr02@cair-cas.org.hk。邮件主题请注明应聘[博士后/助理研究员（多模态医学大模型方向）]-[姓名]。