PhD and Postdoc Positions in AI/ML for Biomedical Science at Columbia University Columbia University in United States

The Laboratory of AI and Biomedical Science (LABS) at Columbia University is actively recruiting PhD students and postdoctoral researchers. The lab, led by Assistant Professor Junhao (Hao) Wen, focuses on developing and applying advanced AI and machine learning (AI/ML) methodologies to analyze biomedical data, particularly in the context of multi-omics and multi-organ studies related to human aging and diseases such as Alzheimer's. LABS emphasizes the integration of statistical and AI/ML techniques with multi-modal data, including MRI, genetics, metabolomics, and proteomics, to address clinically relevant problems in precision medicine.

Research directions in the lab include the application of AI/ML to 'big data' in biomedical science, with a strong focus on neuroimaging, genomics, and genetics. The lab encourages candidates with backgrounds in computer science, biomedical engineering, applied mathematics, neuroscience, and related quantitative fields. Experience with programming languages such as Linux, Python, and R is required, and candidates with expertise in neuroimaging, machine learning, or genomics/genetics are particularly encouraged to apply.

Applicants should possess excellent communication and writing skills. The lab is committed to diversity and encourages applications from underrepresented individuals and students. The application deadline for the Columbia BME PhD program is December 15, 2025. Interested candidates should send their CV to [email protected] or [email protected] and are encouraged to review the lab's website for further information.

Columbia University, located in the United States, offers a vibrant research environment and access to cutting-edge resources in biomedical science and engineering. The LABS group collaborates with institutions such as the New York Genome Center and Penn, providing a multidisciplinary setting for innovative research in AI/ML, biomedical engineering, and neuroscience.