Several immediate openings exist for postdoctoral positions intended for highly motivated individuals to work with Dr. Qingyu Chen at the Section of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University. These positions entail projects related to data science and artificial intelligence (AI) in healthcare, covering biomedical natural language processing, medical image analysis, and AI-assisted healthcare applications.
Required Qualifications:
- Possession of a Ph.D. in biomedical informatics, computer science, or related fields.
- Demonstration of first-authored papers in relevant areas, including but not limited to biomedical natural language processing, medical image analysis, or AI-assisted healthcare applications.
- Proficiency in programming, particularly in deep learning tools such as PyTorch and TensorFlow.
- Preferred experience in interdisciplinary research.
Application Process:
The review of applications will commence immediately and proceed on a rolling basis until all positions are filled. Interested candidates should submit a letter of interest, a CV, and the contact information for three professional references to [email protected]. Please use “Postdoctoral Application in Artificial Intelligence and Data Science in Healthcare” as the subject line.
About Dr. Qingyu Chen:
Dr. Qingyu Chen is an incoming assistant professor at the Section of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University. He is currently finalizing the K99 phase and will be establishing the team in 2024. Dr. Chen has led research in AI and data science in healthcare, contributing over 40 first-authored papers out of over 60 in total. Additionally, he has developed widely-used biomedical informatics tools such as LitCovid (Chen et al., Nature 2020; Chen et al., Nucleic Acids Research 2021; Chen et al., Nucleic Acids Research 2023), which has been used by millions of biomedical researchers and healthcare professionals worldwide.
Dr. Chen is the recipient of the K99 grant on multimodal AI-assisted disease diagnosis and has received several competitive awards, including the NIH Fellows Award for Research Excellence (twice), recognition as a Top 50 Talent in AI across disciplines by Baidu Scholar, the Microsoft Master Innovation Award, Excellence in Teaching Awards (twice), the NIH Mentor Award (four times), and the top performance award in three machine learning challenge tasks in biomedical informatics as the first author.