Postdoctoral Researcher in Data Science for Cancer Research and Precision Prevention

National Cancer Institute, National Institutes of Health
Division of Cancer Epidemiology and Genetics (DCEG)
United States Washington DC metro Rockville, Maryland


The new Data Science Group ( created at the Division of Cancer Epidemiology and Genetics (DCEG) of the National Cancer Institute in 2019 is opening postdoctoral fellowship positions* in research projects ranging from distributed Machine Learning to Computational Pathology and Population Science. These are technology and data-intensive intensive projects that explore computational solutions at the consumer-facing intersection of Cloud and Web computing.

DCEG is involved in cohort studies, both national and international, that involve hundreds of thousands of participants**. The data types are constantly evolving and range from genomics and digital pathology to environmental and behavioral signals. The technology landscape is evolving just as fast, with wearable sensing, consumer-facing health services creating entirely new opportunities to research and develop Precision Prevention of Cancer. Self-directed and community-driven Education plays a major role in the configuration of these positions. The candidates selected will be invited to contribute to hackathons such as If you like this line of research but prefer the software engineering complement, please have a look at


** This position will engage the new data landscape being populated by three of the newest cohort studies:,,


A doctoral degree with an emphasis in Bioinformatics, Computational Statistics, Computer Science, Media Science or Data Science. Candidates familiar with neural network based AI, Web and Cloud Technologies or with an interest in exploring AI-first software engineering applications to cancer research and prevention will be favored. These positions welcome both national and non-resident candidates. Additional information about hiring, career advancement and benefits can be found at

Start date

As soon as possible

How to Apply

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