Academician Dai Qionghai is a professor in the Department of Automation at Tsinghua University, an adjunct professor at the School of Life Sciences, an academician of the Chinese Academy of Engineering, the chairman of the China Artificial Intelligence Society, the dean of the School of Information, and the dean of the Institute of Brain and Cognitive Sciences at Tsinghua University. He has long been engaged in interdisciplinary research in fields such as computational photography, optics, brain and cognitive science, and artificial intelligence. Under his leadership, the Imaging and Intelligent Technology Laboratory in the Department of Automation has adhered to a research philosophy of integrating scientific thinking with engineering practice and practicing original innovation in interdisciplinary fields for twenty years. The lab has conducted a series of foundational theoretical and key technological research in artificial intelligence, stereoscopic vision, computational imaging, and brain cognition. In recent years, the team has published over 30 high-level papers in Nature, Cell, and their sub-journals.

The team has developed a series of original instruments and equipment, which are widely used and commercialized in the field of biological microscopy. These advancements facilitate the study of life processes at mesoscopic scales, leading to discoveries and breakthroughs in life sciences. The research group now possesses internationally advanced instrumental microscopy technology and systems, both hardware and software, and has been conducting scientific explorations in fields such as neuroscience, immunology, neurodegenerative diseases, and cancer. Several postdoctoral positions are now open for researchers interested in these interdisciplinary studies.

Postdoctoral Position Requirements:

1. **Research Position in Neural Encoding Mechanisms in Live Animals**

- Expertise in understanding the brain's functional mechanisms involving integration of multi-modal information such as vision, hearing, and sensation, with a solid research foundation in the neural mechanisms of brain cognition.

- Proficiency in experimental frameworks in neuroscience, capable of independently designing experiments and conducting data collection.

- Preference for candidates with experience in designing cognitive paradigms based on brain imaging and electrophysiology, as well as large-scale data analysis.

- Applicants should have a background in neurobiology, cognitive neuroscience, psychology, or related fields.

2. **Research Position in Disease and Immunology Mechanisms in Live Animals**

- Deep understanding of the immune system, extensive experience in experimental research on mechanisms or pharmacological treatments of neurological diseases, tumors, or vascular diseases, with significant research outcomes.

- Knowledge of brain immunity or peripheral organ immunity, strong interest in long-term dynamic observation and multi-information tracking in live subjects, and ability to quickly engage in experimental design and data acquisition.

- Applicants should have a background in immunology, biology, pharmacology, life sciences, or related fields.

3. **Research Position in Computational Neuroscience and Artificial Intelligence**

- Strong foundation in large-scale data analysis, particularly in interpreting live brain imaging data, skilled in using deep learning and neural computational modeling for large data analysis, with experience in complex network modeling and brain-inspired intelligence.

- Keen perception of large-scale, large-sample data in live subjects and a strong interest in exploring biological mechanisms and mathematical patterns in live animals.

- Applicants should have a background in computational neuroscience, artificial intelligence, computer science, mathematics, or related fields.

4. **Research Position in Optical Engineering and Computational Optics**

- Experience in constructing microscopic optical paths, involved in research and development of brain imaging equipment.

- Published high-level research in fields such as artificial intelligence, computer vision, natural language processing.

- Applicants should have a background in optical engineering, computational optics, or related fields.

Application Requirements:

1. Candidates must hold a doctoral degree, demonstrate excellent academic and personal conduct, be in good health, be under 35 years of age, and generally have received their doctoral degree within the last three years.

2. Candidates should possess independent research capabilities and a good team spirit, show initiative in taking responsibility, have strong communication and coordination skills, be able to handle pressure well, and have an interest in interdisciplinary research.

3. Applicants should have published at least one high-level paper as the first author in the relevant academic fields mentioned above.

4. Number of positions available: Several

Position Benefits:

1. Salary and insurance will follow national regulations and Tsinghua University's postdoctoral management guidelines, plus laboratory performance bonuses, with an expected total annual income of 300,000 to 600,000 RMB; exceptional candidates may earn more.

2. Provision of Tsinghua University postdoctoral apartments or a housing subsidy.

3. Access to Tsinghua University policies for children's education and healthcare for faculty members.

4. Opportunities to apply for various scientific funds and postdoctoral support programs, including the Postdoctoral Science Fund, Postdoctoral Innovation Talent Support Program (600,000 RMB), international postdoctoral exchange programs, and Tsinghua University's "Shuimu Scholar" program (300,000 RMB). For more details, please visit the official Tsinghua University postdoctoral website: http://postdoctor.tsinghua.edu.cn/.

Application Materials:

Interested applicants should send a detailed CV including complete educational and professional experience, main research work, and a list of publications to rfang@tsinghua.edu.cn. Please specify "Name - Postdoctoral Application" in the subject of the email. Candidates who pass the preliminary selection will be contacted for an interview. Those not selected will not be notified further.

Application Deadline: June 30, 2024.