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Postdoctoral Research Scientist
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Columbia University's Mailman School of Public Health, renowned for its pioneering research and advanced learning environment, is a vital part of Columbia University's Medical Campus. Located within Columbia University's expansive Medical Campus in Manhattan, New York City, it offers unparalleled opportunities for collaboration, research, and professional growth in the heart of a vibrant urban setting.
A Postdoctoral Research Scientist position is now open in Dr. Wenpin Hou’s research group within the Department of Biostatistics at Columbia University. Our team is at the forefront of developing innovative computational and statistical methods to analyze intricate data types in genomics and data science. This includes areas such as single-cell genomics, epigenomics, and spatial transcriptomics. Our ultimate aim is to deepen our understanding of gene regulation and enhance human health. We seek candidates who possess a solid foundation in any of these areas: computational genomics, functional data analysis, network modeling, spatiotemporal data modeling, deep learning and transformers, time series analysis, or related domains. Those eager to apply their expertise to address pressing challenges in genomics and health are particularly encouraged to apply. The selected individual will collaborate closely with Dr. Hou and esteemed colleagues from Columbia University, Johns Hopkins University, and New York University. They will be instrumental in devising and implementing state-of-the-art methods on expansive datasets from sources like NIH-funded initiatives and major consortium projects. This role offers the chance to spearhead and co-author influential publications, showcase findings at renowned conferences, and acquire invaluable experience in statistical machine learning as applied to single-cell genomics, multi-omics, and spatial transcriptomics. Additionally, the candidate will benefit from mentorship in career progression and grant writing, including guidance on securing awards like the NIH K99/R00.
Applicants should have a PhD degree or equivalent in computer science, biostatistics, statistics, mathematics, biomedical engineering, or related fields. Applicants should also have excellent programming skills (e.g., R, Python) and communication skills.