Programmer/Analyst in Data Science and Engineering for Cancer Precision Prevention

National Cancer Institute, National Institutes of Health
Division of Cancer Epidemiology and Genetics (DCEG)
United States Maryland Washington DC metro, Rockville
dceg.cancer.gov/about/staff-directory/biographies/A-J/almeida-jonas

Description

The new Data Science Group created at the Division of Cancer Epidemiology and Genetics (DCEG) of the National Cancer Institute in 2019 is opening programmer/analyst positions in software development for research projects. DCEG is involved in long-term 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 and AI creating entirely new opportunities to research and develop Precision Prevention of Cancer. Accordibngly self-directed and community-driven carreer advancement plays a major role in the configuration of these positions. The candidates selected will be invited to contribute to hackathons such as cloud4bio.github.io.

* Candidates selected will play a key role in defining the data-intensive computational landscape defined by three of the newest cohort studies: dceg.cancer.gov/research/who-we-study/cohorts/connect, dceg.cancer.gov/confluence, dceg.cancer.gov/research/cancer-types/lung/sherlock-lung-study.


Qualifications

These are technology-intensive and data-intensive intensive projects that explore computational solutions at the consumer-facing intersection of Cloud and Web computing. Familiarity with the serverless execution model of Cloud Computing (FaaS) as wel as with progressive web applications (PWA) are strongly favored. Familiarity with deep learning and other multivariate machine learning approaches are also significant selection criteria. Specifically, these are DevOps positions with a focus on client-side and server-side JavaScript programming (PWA + nodejs FaaS). Familiarity with Python-based environemnts for machine learning and more generically with TensorFlow are also favored. Candidates are expected to have a degree in CS, CSE, Data Science or Bioinformatics but self-taught candidates wth DevOps experience are also welcome, particulalry if familiar with the biomedical domain of application development.


Start date

As soon as possible

Start date

To be determined

How to Apply

email to jonas.dealmeida@nih.gov with cc to geeta.joshi@nih.gov


Contact

Jonas Almeida