The Bo Xia Lab at the Broad Institute of MIT and Harvard, in collaboration with Massachusetts General Hospital and Harvard Medical School, is recruiting multiple postdoctoral scholars and graduate students to join its interdisciplinary research team. The lab focuses on understanding, predicting, and designing cellular rules using biologically grounded multimodal AI technologies. Research areas include genome regulation, cell fate determination, synthetic biology, aging, cancer biology, stem cell and regenerative biology, immunology, and molecular neuroscience.

Successful candidates will work on multimodal machine learning, generative AI, single-cell multi-omics, computational systems biology, and synthetic biology applied to health and disease. The lab has developed foundational AI models such as C.Origami and Chromtrion to accelerate biological discoveries and continues to pioneer next-generation cell engineering and de novo cell type design.

Applicants should have a PhD in computer science, data science, computational biology, or related fields (for computation-focused roles), or a PhD in broadly defined biomedical sciences (for experiment-focused roles). Strong programming skills and experience with machine learning frameworks (e.g., PyTorch, TensorFlow) are required for computational candidates. Expertise in multimodal machine learning, generative AI, and agentic models is highly encouraged. Experimental candidates should have research expertise in single-cell genomics, gene regulation, synthetic genetics, aging biology, stem cell and regenerative biology, cancer biology, immunology, or molecular neuroscience.

The lab values independent research motivation, problem-solving ability, and enthusiasm for multidisciplinary collaboration. Funding details are not specified, but positions are at top-tier institutions known for competitive support. To apply, email [email protected] with your CV and a brief description of your background, research interests, and career goals. Selected candidates will be invited for an initial Zoom or in-person interview, and reference letters will be requested at a later stage.

For more information, visit boxialab.org/join-us.