Job Summary

We seek an outstanding candidate passionate about advancing the ability to acquire and then reason over epidemiological, environmental, and social data sources with the goal of developing disease surveillance platforms around the world to support public health decision makers. The candidate will have experience obtaining and analyzing epidemiological and relevant environmental information from: historical weather records, environmental, socio-economic and population density, Internet-based data sources, etc. Ideally, the candidate should have strong quantitative backgrounds and a history of innovative approaches to computational methods (and mathematical modeling) applied to public health and other relevant fields, specifically, the candidate will have ample experience designing and implementing statistical (including machine learning) methods that leverage big data sources such as: human mobility patterns, geo-tagged Twitter microblogs, environmental determinants, to monitor disease activity.

The candidates will join the Machine Intelligence Group for the betterment of Health and the Environment (MIGHTE) led by Prof. Mauricio Santillana as a Postdoctoral Associate.

Minimum Qualifications

The candidate must have a doctoral degree (MD, PhD, MD/PhD, or equivalent), a strong record of publishing, and promise to achieve independent funding.

Key Responsibilities & Accountabilities

60% Assist in initiating, executing, and completing research

25% Prepare and write research papers, presentations, grant proposals, etc.

10% Lab management

5% Train graduate students

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