The Tang Lab at the University of British Columbia is recruiting multiple postdoctoral fellows and PhD students to advance research in AI for Life Sciences, Computational Neuroscience, and Biomedical Research. The lab focuses on developing interpretable and autonomous AI for multi-scale and multi-modal spatiotemporal biology, including single-cell, spatial, and multi-omics data, with applications in neuroscience, brain-computer interfaces, and cancer genomics. The research environment is highly collaborative, diverse, and stimulating, with access to high-performance GPUs and rich datasets.

Three postdoctoral positions are available: (1) AI for Biology, focusing on next-generation computational and machine-learning frameworks for single-cell, spatial, and multi-modal omics; (2) Computational Neuroscience and Multimodal AI, emphasizing large-scale neural recording, multimodal representation learning, and brain-inspired AI; and (3) Reinforcement Learning and Autonomous Laboratory Systems, developing decision-making algorithms for autonomous laboratory platforms. Expertise in deep learning, representation learning, uncertainty quantification, computer vision, reinforcement learning, robotics, and explainable AI is sought. A biomedical background is not required for any position.

PhD positions are open to students interested in developing AI and machine learning methods or applying AI to biomedical research. Applicants should have a strong programming and AI background; exceptional students without biological experience are considered. The lab recruits from several UBC graduate programs, including Computer Science, Genome Science + Technology, and Bioinformatics. The application deadline for graduate programs is December 15, while postdoctoral applications are accepted until February 15, 2026.

Funding for these positions is provided by prestigious grants such as the NSERC Discovery Grant, Canada Research Chair Tier 2, and the John R. Evans Leaders Fund from CFI. The lab is located in Vancouver, offering a vibrant city life alongside natural beauty. Interested candidates should email Prof. Xin Tang with their CV and a brief description of research interests. For postdoctoral roles, include a GitHub account, a one-page research highlights letter, and contact information for three references. Applications are reviewed on a rolling basis, and formal applications can be submitted via the lab website.

For more information, visit Tang Lab and Join Us. The lab welcomes undergraduate, master's, and visiting scholars, with preference for those with AI/ML coursework and commitment to long-term research involvement.