Prospective postdoctoral research fellows: I am seeking motivated postdoctoral research fellows with strong expertise in statistics, statistical learning, and computational methods.
The fellows will develop integrative statistical and machine learning methods for cancer and Alzheimer’s disease and related dementias risk prediction using data from multiple institutions, with particular emphasis on addressing population, institutional, and data-source heterogeneity. The research will involve large-scale electronic health record data (EHR), genetic and genomic data, and deeply phenotyped biobank cohorts, including linked EHR–biobank resources.
Additional projects may involve large language models, natural language processing, multimodal learning, medical imaging, and the integration of structured clinical variables, longitudinal EHR data, genomics, clinical text, and imaging data. Candidates with prior experience analyzing EHR, genetic, genomic, imaging, or biobank data are particularly encouraged to apply.
Successful candidates will join a vibrant research environment at Columbia University, working closely with Dr. Iuliana Ionita-Laza and the Translational AI Laboratory (TRAIL4Health) led by Dr. Ying Wei.
Prospective master's students: Please read about our projects and think about how your expertise and past experience could add to our team. If you are interested, please email me your CV and a one-paragraph description of your qualifications for potential opportunities.
Prospective PhD students: PhD applications in our department are reviewed by a PhD admission committee. The selected applicants will be invited for the on-site interview in January or February. I look forward to discussing the opportunity of being your mentor once you are admitted.