Data Science for Cancer Research and Precision Prevention – Postdoctoral Fellowship
The Data Science & Engineering Research Group within the NCI Division of Cancer Epidemiology and Genetics (DCEG) is seeking candidates for postdoctoral fellowships in research projects ranging from distributed machine learning to computational pathology and population science. These are technology and data-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 and consumer-facing health services creating entirely new opportunities to research and develop precision prevention of cancer. Self-directed and community-driven education play a major role in the configuration of these positions. Fellows will contribute to hackathons such as cloud4bio.github.io.
Goals: This position will engage the new data landscape being populated by three of the newest studies, the Connect study, the Confluence project and Sherlock-lung (a genomic epidemiologic study of lung cancer in never smokers).
Qualifications: A doctoral degree with an emphasis in bioinformatics, computational statistics, computer science, media science or data science. Candidates familiar with neural network-based artificial intelligence (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 U.S. and non-resident candidates.
For more information about the position, contact Jonas Almeida, Ph.D., Chief Data Scientist.
To apply: See the Division Fellowship Information page for an overview, qualifications, and application details.