With any of the following research directions:
1.Application of AI in the field of reproduction.
2. Low-altitude cross-domain unmanned systems.
3. Adaptive control, intelligent systems and artificial intelligence.
4. Rehabilitation training robots.
5. Surgical robots.
6. Humanoid robots.
7. Intelligent transportation.
8. Intelligent medical diagnosis and treatment with embodied intelligence as the core.
9. Multimodal foundation models for medical artificial intelligence.
10. Research on trusted autonomous driving strategy learning in complex urban environments.

1. Professional Background:
- Possess a doctoral degree in related majors such as biomedical engineering, artificial intelligence, automation, machinery, electronics, computer science, and communications.
- Interdisciplinary background applicants are warmly welcomed, especially candidates with a solid technical foundation and a desire to develop in interdisciplinary fields.

2. Research Goals:
- Aim to solve practical technical problems of enterprises and commit to promoting the industrial application of scientific research achievements; be passionate about transforming innovative technologies into market products and willing to participate in the complete process from conceptual design to commercial implementation;
- Have a keen insight into enterprise needs and technical pain points, and be able to combine theory and practice to propose practical solutions.

3. Ability Requirements:
- Have strong scientific research and innovation capabilities, able to carry out independent research and put forward innovative solutions;
- Possess excellent team spirit, able to communicate and cooperate efficiently in interdisciplinary teams;
- Have the ability to implement technologies, able to transform research results into actual products or solutions to meet the real needs of enterprises.

4. Preferred Qualifications:
- Have relevant industry experience and have participated in enterprise cooperation projects, technical development or industrialization-related work;
- Focus on practical application scenarios in academic research, have published high-level papers related to enterprise needs or have patent experience;
- Candidates with innovation and entrepreneurship experience or excellent performance in well-known technological innovation competitions are preferred.