Imagine a dynamic dataset that encompasses comprehensive information about a patient in the health care system: what diseases they have, their genomic sequence, their social media messages (e.g, tweets and likes), and where they live. How would you—a data hacker—store, retrieve, and analyze this information to drive biomedical discovery to find a new way of predicting disease or even a new therapy for a disease? Chirag Patel’s Group at the Department of Biomedical Informatics at Harvard Medical School is looking for a data engineer to build cutting-edge platforms and data infrastructure to enable large-scale data-driven research to address this question. We aim to integrate diverse data sources from geotemporal information (e.g., NOAA Weather Data, EPA AirData), individual genomic sequence, social media data, and health claims information to paint a comprehensive picture of individuals who are sick and healthy.
First, the Biomedical Data Scientist Postdoctoral Associate will aggregate publicly available data sources from numerous sources. The Data Scientist will apply statistical machine learning algorithms for prediction and discovery of clinical, genetic, and environmental factors related to disease.
The diversity of subject matter will require a creative mind and a candidate capable of deploying imaginative strategies and who is dedicated to solving complex and challenging problems within an interdisciplinary environment.
Candidates must have a PhD in computer science, mathematics, physics, biomedical informatics, bioinformatics, computer science, or a related quantitative field.
The position is available immediately and can be renewed annually.
How to apply
Email applications including curriculum vitae, summary statement of personal objectives, and the names and email addresses of 2-3 references to Chirag Patel (firstname.lastname@example.org).
Harvard Medical School is an Equal Opportunity/Affirmative Action Employer.
Women and minorities are especially encouraged to apply.