Current Vacancies

Research Assistant - Embodied Continual Learning and Multimodal Large Language Model Research

研究助理-具身持续学习与多模态大模型研究

Job Responsibilities

1. Design continual learning algorithms for real-world medical scenarios to address long-tail and forgetting problems.

2. Develop continual fine-tuning and reinforcement fine-tuning methods for MLLMs, optimizing model architectures and training strategies.

3. Regularly report research progress to the team and maintain close communication and collaboration with team members.

4. Write high-quality research reports, academic papers, and patent application materials.

Requirements

1. Relevant majors including Computer Science, Artificial Intelligence, Mathematics, etc. Ph.D. candidates, excellent master's or bachelor's degree holders.

2. Strong interest in scientific research, high self-motivation, and the ability to solve problems independently.

3. Proficient in Python and Pytorch, with solid programming foundations.

4. Basic knowledge of LLM, MLLM (e.g., LLaVA, Qwen-VL), MoE, reinforcement learning, etc.

5. Prior experience in large model related projects or publications in top AI conferences are preferred.

Application Method

Please submit CV to hr02@cair-cas.org.hk. The subject of the email should be marked as Application for [Research Assistant - Embodied Continual Learning and Multimodal Large Language Model Research]-[Name].

岗位职责

1. 设计面向实际医疗场景的持续学习算法、克服长尾和遗忘问题。

2. 针对多模态大模型，设计持续微调、强化微调方法，优化模型结构和训练策略。

3. 定期向团队汇报研究进展，与团队成员保持密切沟通与协作。

4. 撰写高质量的学术论文及专利申请。

职位要求

1. 计算机、人工智能、数学等相关专业，博士生、优秀硕士或本科毕业生。

2. 对科研有浓厚的兴趣，自驱力强并且具有独立解决问题的能力。

3. 熟练Python，Pytorch编程，具备扎实的编程基础。

4. 具备LLM, MLLM (如LLaVA, Qwen-VL)，MoE、强化学习等基础知识。

5. 参与过大模型相关项目、发表过大模型相关研究AI顶会论文优先。

申请方式

请将个人简历发送至hr02@cair-cas.org.hk。邮件主题请注明应聘[研究助理-具身持续学习与多模态大模型研究]-[姓名]。